Assessment of state-of-the-art models for predicting the remobilisation of radionuclides following the flooding of heavily contaminated areas: the case of Pripyat River floodplain

The performances of models are assessed to predict the wash-off of radionuclides from contaminated flooded areas. This process should be accounted for in the proper management of the aftermath of a nuclear accident. The contamination of the Pripyat River water following the inundation of a floodplain heavily contaminated by (90)Sr and (137)Cs of Chernobyl origin is used as the basis for modelling. The available experimental evidence demonstrated that remobilisation of radiostrontium is an important process implying a significant secondary radioactive load of water flowing over the contaminated floodplain. On the contrary, there is no empirical evidence of a similar behaviour for radiocaesium. In general, state-of-the-art models properly predicted the remobilisation of strontium, whereas they significantly overestimated radiocaesium concentrations in water. The necessary model improvements for a more accurate prediction of radiocaesium contamination levels include a reassessment of the values of the model parameters controlling the remobilisation process.     

Adult-supervised practice driving for adolescent learners: The current state and directions for interventions

IntroductionThe aim of this study was to quantify and identify correlates to the amount of parent-supervised behind-the-wheel practice hours by novice teen drivers.MethodsA national survey of 945 parents of recently licensed teen drivers was conducted. Multivariate logistic regression was used to identify factors related to the number of practice hours completed.ResultsSixty-one percent of parents reported practicing 50 or more hours with their teen. Two-parent involvement was associated with more practice hours, though use of a professional driving instructor was not. Parents of teens licensed in states mandating 50 or more hours of practice driving were more likely to report at least 50 practice hours than those in states mandating 20–40 hours or in states without mandates.Impact on IndustryThe findings underscore the integral role of parents in the learning to drive process and provide further support for GDL requirements for practice hours.     

Transfer of Graphene CVD to Surface of Low Density Polyethylene (LDPE) and Poly(butylene adipate-co-terephthalate) (PBAT) Films: Effect on Biodegradation Process

Here, the influence of graphene as a coating on the biodegradation process for two different polymers is investigated, poly(butylene adipate-co-terephthalate) (PBAT) (biodegradable) and low-density polyethylene (LDPE) (non-biodegradable). Chemical vapor deposition graphene was transferred to the surface of two types of polymers using the Direct Dry Transfer technique. Polymer films, coated and uncoated with graphene, were buried in a maturated soil for up to 180 days. The films were analyzed before and after exposure to microorganisms in order to obtain information about the integrity of the graphene (Raman Spectroscopy), the biodegradation mechanism of the polymer (molecular weight and loss of weight), and surface changes of the films (atomic force microscopy and contact angle). The results prove that the graphene coating acted as a material to control the biodegradation process the PBAT underwent, while the LDPE covered by graphene only had changes in the surface properties of the film due to the accumulation of solid particles. Polymer films coated with graphene may allow the production of a material that can control the microbiological degradation, opening new possibilities in biodegradable polymer packaging. Regarding the possibility of graphene functionalization, the coating can also be selective for specific microorganisms attached to the surface.     

Variation in posture quality across musical instruments and its impact during performances

Objective. Bad posture increases the risk that a musician may suffer from musculoskeletal disorders. This study compared posture quality required by different instruments or families of instruments. Methods. Using an ad-hoc postural observation instrument embracing 11 postural variables, four experts evaluated the postures of 100 students attending a Spanish higher conservatory of music. Results. The agreement of the experts’ evaluations was statistically confirmed by a Cohen's κ value between 0.855 and 1.000 and a Kendall value between 0.709 and 1.000 (p?χ² tests revealed significant association between instrument families and seated posture with respect to pelvic attitude, dorsal curvature and head alignment in both sagittal and frontal planes. This analysis also showed an association between instrument families and standing posture with respect to the frontal plane of the axis of gravity, pelvic attitude, head alignment in the frontal plane, the sagittal plane of the shoulders and overall posture. Conclusions. While certain postural defects appear to be common to all families of instruments, others are more characteristic of some families than others. The instrument associated with the best posture quality was the bagpipe, followed by percussion and strings.     

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.