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Collisions between bicycles and motor vehicles are one of the leading risk factors for injury and death in childhood and adolescence. We examined longitudinal and concurrent effortful control (EC) as predictors of risky bicycling behavior in early- to mid-adolescence, with age and gender as moderators. We also examined whether EC was associated with parent-reported real-world bicycling behavior and all lifetime unintentional injuries.

Parent-reported EC measures were collected when children (N = 85) were 4 years old and when they were either 10 years (N = 42) or 15 years (N = 43) old. We assessed risky bicycling behavior by asking the adolescents to bicycle across roads with high-density traffic in an immersive virtual environment. Parents also reported on children’s real-world bicycling behavior and lifetime unintentional injuries at the time of the bicycling session.

We found that both longitudinal and concurrent EC predicted adolescents’ gap choices, though these effects were moderated by age and gender. Lower parent-reported early EC in younger and older girls predicted a greater willingness to take tight gaps (3.5 s). Lower parent-reported concurrent EC in older boys predicted a greater willingness to take gaps of any size. Children lower in early EC started bicycling earlier and were rated as less cautious bicyclists as adolescents. Adolescents lower in concurrent EC were also rated as less cautious bicyclists and had experienced more lifetime unintentional injuries requiring medical attention.

Early measures of child temperament may help to identify at-risk populations who may benefit from parent-based interventions.

 

McCormick’s relaxation technique is one of the most versatile and commonly used methods for computing the convex relaxations necessary for deterministic global optimization. The core of the method is a set of rules for propagating relaxations through basic arithmetic operations. Computationally, each rule operates on four-tuples describing each input argument in terms of a lower bound value, an upper bound value, a convex relaxation value, and a concave relaxation value. We call such tuples McCormick objects. This paper extends McCormick’s rules to accommodate input objects that are empty (i.e., the convex relaxation value lies above the concave, or both relaxation values lie outside the bounds). Empty McCormick objects provide a natural way to represent infeasibility and are readily generated by McCormick-based domain reduction techniques. The standard McCormick rules are strictly undefined for empty inputs and applying them anyway can yield relaxations that are non-convex/concave on infeasible parts of their domains. In contrast, our extended rules always produce relaxations that are well-defined and convex/concave on their entire domain. This capability has important applications in reduced-space global optimization, global dynamic optimization, and domain reduction. 

We addressed the hypothesis that intraspecific genetic variation in plant traits from different sites along a distance/elevation gradient would influence the communities they support when grown at a new site. Answers to this hypothesis are important when considering the community consequences of assisted migration under climate change; i.e., if you build it will they come?. We surveyed arthropod communities occurring on the foundation riparian tree species Populus angustifolia along a distance/elevation gradient and in a common garden where trees from along the gradient were planted 20–22 years earlier. Three major patterns were found: 1) In the wild, arthropod community composition changed significantly. Trees at the lower elevation site supported up to 58% greater arthropod abundance and 26% greater species richness than more distant, high elevation trees. 2) Trees grown in a common garden sourced from the same locations along the gradient, supported arthropod communities more similar to their corresponding wild trees, but the similarity declined with transfer distance and elevation. 3) Of five functional traits examined, leaf area, a trait under genetic control that decreases at higher elevations, is correlated with differences in arthropod species richness and abundance. Our results suggest that genetic differences in functional traits are stronger drivers of arthropod community composition than phenotypic plasticity of plant traits due to environmental factors. We also show that variation in leaf area is maintained and has similar effects at the community level while controlling for environment. These results demonstrate how genetically based traits vary across natural gradients and have community-level effects that are maintained, in part, when they are used in assisted migration. Furthermore, optimal transfer distances for plants suffering from climate change may not be the same as optimal transfer distances for their dependent communities. 

The phenomenon of pulsar nulling, observed as the temporary inactivity of a pulsar, remains poorly understood both observationally and theoretically. Most observational studies that quantify nulling employ a variant of Ritchings algorithm, which can suffer significant biases for pulsars where the emission is weak. Using a more robust mixture model method, we study pulsar nulling in a sample of 22 recently discovered pulsars, for which we publish the nulling fractions for the first time. These data clearly demonstrate biases of the former approach and show how an otherwise nonnulling pulsar can be classified as having significant nulls. We show that the population-wide studies that find a positive correlation of nulling with pulsar period/characteristic age can similarly be biased because of the bias in estimating the nulling fraction. We use our probabilistic approach to find the evidence for periodicity in the nulls in a subset of three pulsars in our sample. In addition, we also provide improved timing parameters for 17 of the 22 pulsars that had no prior follow-up.

 

Recolonization of predators to their former ranges is becoming increasingly prevalent. Such recolonization places predators among their prey once again; the latter having lived without predation (from such predators) for a considerable time. This renewed coexistence creates opportunities to explore predation ecology at both fundamental and applied levels. We used a paired experimental design to investigate white‐tailed deer risk allocation in the Upper and Lower Peninsulas (UP and LP) in Michigan, USA. Wolves are functionally absent in the LP, while deer in the UP coexist with a re‐established wolf population. We treated 15 sites each in UP and LP with wolf olfactory cues and observed deer vigilance, activity, and visitation rates at the interface of habitat covariates using remote cameras. Such a paired design across wolf versus no‐wolf areas allowed us to examine indirect predation effects while accounting for confounding parameters such as the presence of other predators and human activity. While wolf urine had no effect across most metrics in both UP and LP, we observed differences in deer activity in areas with versus without wolves. Sites treated with wolf urine in the UP showed a reduction in crepuscular deer activity, compared to control/novel‐scent treated sites. Furthermore, we observed a strong positive effect of vegetation cover on deer vigilance in these sites. This indicates that simulated predator cues likely affect deer vigilance more acutely in denser habitats, which presumably facilitates predation success. Such responses were however absent among deer in the LP that are presumably naïve toward wolf predation. Where human and non‐human predators hunt shared prey, such as in Michigan, predators may constrain human hunting success by increasing deer vigilance. Hunters may avoid such exploitative competition by choosing hunting/bait sites located in open areas. Our results pertaining to fundamental predation ecology have strong applied implications that can promote human–predator coexistence.

 

Staphylococcus aureus uses small peptides to assess its population densisty ( i.e. , quorum sensing) and regulate virulence at high cell number. Here, we report the design and synthesis of peptidomimetics based on these native signals that strongly block this communication pathway in all four specificity groups of S. aureus . 

In many automated motion planning systems, vehicles are tasked with tracking a reference path or trajectory that is safe by design. However, due to various uncertainties, real vehicles may deviate from such references, potentially leading to collisions. This paper presents rigorous reachable set bounding methods for rapidly enclosing the set of possible deviations under uncertainty, which is critical information for online safety verification. The proposed approach applies recent advances in the theory of differential inequalities that exploit redundant model equations to achieve sharp bounds using only simple interval calculations. These methods have been shown to produce very sharp bounds at low cost for nonlinear systems in other application domains, but they rely on problem-specific insights to identify appropriate redundant equations, which makes them difficult to generalize and automate. Here, we demonstrate the application of these methods to tracking problems for the first time using three representative case studies. We find that defining redundant equations in terms of Lyapunov-like functions is particularly effective. The results show that this technique can produce effective bounds with computational times that are orders of magnitude less than the planned time horizon, making this a promising approach for online safety verification. This performance, however, comes at the cost of low generalizability, specifically due to the need for problem-specific insights and advantageous problem structure, such as the existence of appropriate Lyapunov-like functions.