Factors associated with driving under the influence of alcohol

Objective: This study examined the risk factors of driving under the influence of alcohol (DUI) among drivers of specific vehicle categories (DSC). On the basis of this research, the variables related to DUI and involvement in traffic crashes were defined. The analysis was conducted for car drivers, bicyclists, motorcyclists, bus drivers, and truck drivers.

Method: The research sample included drivers involved in traffic crashes on the territory of Serbia in 2016 (60,666). Two types of analyses were conducted in this study. Logistic regression established the correlation between DUI and DSC and the The Technique for Order of Preference by Similarity to Ideal Solution (Multi-criteria decision making) method was applied to consider the scoring and explore the potential for the prevalence of DUI on the basis of 2 data sets (DUI and non DUI).

Results: The study results showed that driver error and male drivers were the 2 most significant risk factors for DUI, with the highest scores and potential for prevalence. The nonuse of restraint systems, driver experience, and driver age are the factors with a significant prediction of involvement in an accident and an insignificant prediction of DUI.

Conclusions: Following the development of the logistic prediction models for DUI drivers, testing of the model was conducted for 3 control driver groups: Car, motorcycle, and bicycle. The prediction model with a probability greater than 50% showed that 77% of car drivers were under the influence of alcohol. Similarly, the prediction percentage for motorcyclists and bicyclists amounted to 71 and 67%, respectively. The recommendation of the study is that drivers whose DUI probability is above 50% should be potentially suspected of DUI. The results of this study can help to understand the problem of DUI among specific driver categories and detect DUI drivers, with the aim of creating successful traffic safety policy.     

Deriving heart rate variability indices from cardiac monitoring—An indicator of driver sleepiness

Objective: Driver fatigue is considered to be a major contributor to road traffic crashes. Cardiac monitoring and heart rate variability (HRV) analysis is a candidate method for early and accurate detection of driver sleepiness. This study has 2 objectives: to evaluate the (1) suitability of different preprocessing strategies for detecting and removing outlier heartbeats and spectral transformation of HRV signals and their impact of driver sleepiness assessment and (2) relation between common HRV indices and subjective sleepiness reported by a large number of drivers in real driving situations, for the first time.

Methods: The study analyzed >3,500 5-min driving epochs from 76 drivers on a public motorway in Sweden. The electrocardiograph (ECG) data were recorded in 3 studies designed to evaluate the physiological differences between awake and sleepy drivers. The drivers reported their perceived level of sleepiness according to the Karolinska Sleepiness Scale (KSS) every 5?min. Two standard methods were used for identifying outlier heartbeats: (1) percentage change (PC), where outliers were defined as interbeat intervals deviating >30% from the mean of the four previous intervals and (2) standard deviation (SD), where outliers were defined as interbeat interval deviating >4 SD from the mean interval duration in the current epoch. Three standard methods were used for spectral transformation, which is needed for deriving HRV indices in the frequency domain: (1) Fourier transform; (2) autoregressive model; and (3) Lomb-Scargle periodogram. Different preprocessing strategies were compared regarding their impact on derivation of common HRV indices and their relation to KSS data distribution, using box plots and statistical tests such as analysis of variance (ANOVA) and Student’s t test.

Results: The ability of HRV indices to discriminate between alert and sleepy drivers does not differ significantly depending on which outlier detection and spectral transformation methods are used. As expected, with increasing sleepiness, the heart rate decreased, whereas heart rate variability overall increased. Furthermore, HRV parameters representing the parasympathetic branch of the autonomous nervous system increased. An unexpected finding was that parameters representing the sympathetic branch of the autonomous nervous system also increased with increasing KSS level. We hypothesize that this increment was due to stress induced by trying to avoid an incident, because the drivers were in real driving situations.

Conclusions: The association of HRV indices to KSS did not depend on the preprocessing strategy. No preprocessing method showed superiority for HRV association to driver sleepiness. This was also true for combinations of methods for frequency domain HRV indices. The results prove clear relationships between HRV indices and perceived sleepiness. Thus, HRV analysis shows promise for driver sleepiness detection.     

Modelling the impacts of land-use and drainage density on the water balance of a lowland–floodplain landscape in northeast Germany

This study presents the modelling approach and impact assessment of different strategies for managing wetland water resources and groundwater dynamics of landscapes which are characterised by the hydrological interactions of floodplains and the adjacent lowlands. The assessment of such impacts is based on the analysis of simulation results of complex scenarios of land-use changes and changes of the density of the drainage-network. The method has been applied to the 198 km² Lower Havel River catchment as a typical example of a lowland–floodplain landscape. The model used consists of a coupled soil water and groundwater model, where the latter one is additionally coupled to the surface channel network. Thus, the hydrological processes of the variable saturated soil zone as well as lateral groundwater flow and the interactions between surface water and groundwater are simulated in an integrated manner. The model was validated for several years of significantly different meteorological conditions. The comparison of lateral and vertical water balance components showed the dominance of lateral flow processes and the importance of the interactions between surface water and groundwater for the overall water balance and the hydrological state of that type of landscape.The simulation of land-use change scenarios showed only minor effects of land-use change on the water balance and groundwater recharge. Changes of groundwater recharge were particularly small within the wetland areas being part of the floodplain where interactions between surface water and groundwater are most pronounced. Alterations in vertical groundwater recharge were counter-balanced by the lateral interaction between groundwater and surface water. More significant deviations in groundwater recharge and storage were observed in the more peripheral areas towards the catchment boundaries which are characterised by greater groundwater distance from the surface and less intense of ground water–surface water interactions.However, the simulation results assuming a coarsening of the drainage network density showed the importance of drainage structure and geometry for the water balance: The removal of the artificial draining ditches in the floodplain would result in significant alterations of total groundwater recharge, i.e., less recharge from winter to early summer and an increase of groundwater recharge during summer and autumn. Furthermore the different effects of groundwater recharge alterations on the dynamics of groundwater stages within the wetland areas close to the floodplains compared to the more peripheral areas could be quantified. Finally, it will be discussed that a well-adjusted co-ordination of different management measures is required to reach a sustainable water resources management of such lowland–floodplain landscapes.     

Estimating the complexity of bird song by using capture-recapture approaches from community ecology

Repertoire size, the number of unique song or syllable types in the repertoire, is a widely used measure of song complexity in birds, but it is difficult to calculate this exactly in species with large repertoires. A new method of repertoire size estimation applies species richness estimation procedures from community ecology, but such capture-recapture approaches have not been much tested. Here, we establish standardized sampling schemes and estimation procedures using capture-recapture models for syllable repertoires from 18 bird species, and suggest how these may be used to tackle problems of repertoire estimation. Different models, with different assumptions regarding the heterogeneity of the use of syllable types, performed best for different species with different song organizations. For most species, models assuming heterogeneous probability of occurrence of syllables (so-called detection probability) were selected due to the presence of both rare and frequent syllables. Capture-recapture estimates of syllable repertoire size from our small sample did not differ significantly from previous estimates using larger samples of count data. However, the enumeration of syllables in 15 songs yielded significantly lower estimates than previous reports. Hence, heterogeneity in detection probability of syllables should be addressed when estimating repertoire size. This is neglected using simple enumeration procedures, but is taken into account when repertoire size is estimated by appropriate capture-recapture models adjusted for species-specific song organization characteristics. We suggest that such approaches, in combination with standardized sampling, should be applied in species with potentially large repertoire size. On the other hand, in species with small repertoire size and homogenous syllable usage, enumerations may be satisfactory. Although researchers often use repertoire size as a measure of song complexity, listeners to songs are unlikely to count entire repertoires and they may rely on other cues, such as syllable detection probability.Communicated by A. Cockburn     

Uptake,distribution and loss of Cr in the crab Xantho hydrophilus

Uptake of ⁵¹Cr(III) is faster than uptake of ⁵¹Cr(VI), but it occurs mainly on the surface of the animals. Steady state is attained after 28 d. The resulting concentration factor is about 200. Although the uptake of ⁵¹Cr(VI) is slower, it is more intensively distributed into the organs and tissues of the animals. Steady state was not attained during the experiments (35 d); the highest concentration factor reached was about 10. The uptake of both ⁵¹Cr(III) and ⁵¹Cr(VI) seems to be passive. For both chemical forms of chromium, the loss rate is inversely proportional to the exposure time. When the uptake lasted longer, owing to the distribution of Cr(VI) into the organs and tissues, the loss rate of Cr(III) is somewhat faster relative to the loss rate of ⁵¹Cr(VI). The opposite is the case when the uptake of both forms lasts only two days. On the basis of the distribution and loss experiments, we argue that hexavalent chromium in living organisms is reduced to the trivalent form and then complexed with organic molecules.     

'Molecular farming' of antibodies in plants

'Molecular farming' is the production of valuable recombinant proteins in transgenic organisms on an agricultural scale. While plants have long been used as a source of medicinal compounds, molecular farming represents a novel source of molecular medicines, such as plasma proteins, enzymes, growth factors, vaccines and recombinant antibodies, whose medical benefits are understood at a molecular level. Until recently, the broad use of molecular medicines was limited because of the difficulty in producing these proteins outside animals or animal cell culture. The application of molecular biology and plant biotechnology in the 1990s showed that many molecular medicines or vaccines could be synthesised in plants and this technology is termed 'molecular farming'. It results in pharmaceuticals that are safer, easier to produce and less expensive than those produced in animals or microbial culture. An advantage of molecular farming lies in the ability to perform protein production on a massive scale using hectares of cultivated plants. These plants can then be harvested and transported using the agricultural infrastructure. Thus, molecular farming allows rapid progress from genetic engineering to crop production, and new cash crops producing recombinant proteins are already being commercially exploited. We speculate that as functional genomics teaches us more about the nature of disease, molecular farming will produce many of the protein therapeutics that can remedy it.     

Hot spots in the bee hive

Honeybee colonies (Apis mellifera) maintain temperatures of 35-36°C in their brood nest because the brood needs high and constant temperature conditions for optimal development. We show that incubation of the brood at the level of individual honeybees is done by worker bees performing a particular and not yet specified behaviour: such bees raise the brood temperature by pressing their warm thoraces firmly onto caps under which the pupae develop. The bees stay motionless in a characteristic posture and have significantly higher thoracic temperatures than bees not assuming this posture in the brood area. The surface of the brood caps against which warm bees had pressed their thorax were up to 3.2°C warmer than the surrounding area, confirming that effective thermal transfer had taken place.     

Preface

Environmental Science and Pollution Research -