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Accurate estimates of mule deer survival are needed to model population dynamics and develop optimal management plans. Survival rates are often estimated using data from radio-collared animals but capture techniques to deploy these collars can risk mortality and injury to the animal. Our objective was to estimate age- and sex-specific survival rates of mule deer in the state of Utah, USA, while also investigating how these rates were affected by capture and handling. We captured 2,977 mule deer throughout the state and fitted them with radio-collars. Using Cox proportional hazard regression, we then estimated survival rates from the collected GPS data. We also examined the effects of age and sex on survival, while accounting for the influence of a variety of other covariates. Finally, we used a model selection framework to evaluate how long survival rates of captured animals were different from those of animals that were not captured. Fawn survival rates were 0.52 (0.45 – 0.60) for females and 0.66 (0.55– 0.79) for males, and overall adult survival rates were 0.76 (0.75 – 0.78) for females and 0.73 (0.70 – 0.77) for males. Survival rates for both sexes varied by age, latitude, and body condition. The negative effect of capture was small and initially disappeared after 3 weeks, but seemed to reappear later, perhaps during periods of high mortality. 

One of the main contributors to the human errors that lead to catastrophic injuries in the construction workplace is the failure to identify hazards as a result of poor attention or cognitive lapses. To address this safety concern, the present study used eye-tracking technology to assess how the association between work experience and hazard identification may be mediated due to inattention. A mediation analysis was conducted and tested using a bias-corrected bootstrapping technique with 5000 resamples. The results estimate the direct and indirect effects of work experience on the hazard identification skills of construction workers observing varying hazardous conditions. The results of the mediation analysis confirm that inattention—demonstrated via inattentiveness toward hazards—mediates the relationship between work experience and hazard identification. Specifically, though work experience and dwell time positively correlate with hazard identification, the direct effect of work experience on hazard identification is attenuated with the inclusion of the mediator variables in the model, thus suggesting attentional impairment offsets the benefits of work experience. The outcomes of this study will enable researchers and safety practitioners to harness real-time eye-movement patterns to identify the precursors of cognitive failure, deficient attentional allocation, and poor visual search strategies, all of which may put workers at risk on construction sites. The results also facilitate the provision of personalized safety feedback to workers and the design of training interventions that will address unique performance deficiencies in workers to prevent the human errors that cause injuries in dynamic environments. 

Cognitive processes have been found to contribute substantially to the human errors that lead to construction accidents. Working memory—a cognitive system with a limited capacity that is responsible for temporarily holding information available for processing—plays an important role in reasoning and decision-making. Since eye movements indicate where a worker directs his/her attention, tracking such movements provides a practical way to measure workers’ attention and comprehension of construction hazards. As a departure in construction industry research, this study correlates attentional allocation with working memory to assess workers’ situation awareness under different scenarios that expose workers to various hazards. To achieve this goal, this study merges research linking eye movements and workers’ attention with research focused on working-memory load and decision making and evaluates what, how, and where a worker distributes his/her attention while performing a task under different working-memory loads. Path analysis models then examined the direct and indirect effect of different working-memory loads on hazard identification performance. The independent variable (working-memory load) is linked to the dependent variable (hazard identification) through the set of mediators (attention metrics). The results showed that the high-memory load condition delayed workers’ hazard identification. The findings of this study emphasize the important role working memory plays in determining how and why workers in dynamic work environments fail to detect, comprehend, and/or respond to physical risks. 

A search for high-mass resonances decaying into a$\tau$-lepton and a neutrino using proton-proton collisions at a center-of-mass energy of$\sqrt{s}=13\mathrm{TeV}$is presented. The full run 2 data sample corresponding to an integrated luminosity of$139{\mathrm{fb}}^{-1}$recorded by the ATLAS experiment in the years 2015–2018 is analyzed. The$\tau$-lepton is reconstructed in its hadronic decay modes and the total transverse momentum carried out by neutrinos is inferred from the reconstructed missing transverse momentum. The search for new physics is performed on the transverse mass between the$\tau$-lepton and the missing transverse momentum. No excess of events above the Standard Model expectation is observed and upper exclusion limits are set on the$W^{\prime }\to \tau \nu$production cross section. Heavy$W^{\prime }$vector bosons with masses up to 5.0 TeV are excluded at 95% confidence level, assuming that they have the same couplings as the Standard Model$W$boson. For nonuniversal couplings,$W^{\prime }$bosons are excluded for masses less than 3.5–5.0 TeV, depending on the model parameters. In addition, model-independent limits on the visible cross section times branching ratio are determined as a function of the lower threshold on the transverse mass of the$\tau$-lepton and missing transverse momentum.