76 research outputs found

    Mitigating Bighorn Sheep–Vehicle Collisions and Habitat Fragmentation with Overpasses and Adaptive Mitigation

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    As transportation infrastructure expands to accommodate increasing human population growth, wildlife–vehicle conflicts (WVCs) are a growing concern for motorist safety and wildlife populations. In the case of large ungulates, minimal information exists on successful mitigation of WVCs involving bighorn sheep (Ovis canadensis) and habitat fragmentation. Too address this void, we evaluated the effectiveness of 3 new wildlife overpasses, 3 culverts, 2 bridges, and ungulate exclusionary fencing as potential desert bighorn sheep (O. c. nelsoni; sheep) crossing opportunities along US Highway 93 in Arizona, USA. We evaluated sheep movements using global positioning system (GPS) radio-transmitter collars and remote cameras for 4 years from March 2011 to March 2015 and sheep–vehicle collision data collected from 2011 to 2020. Although GPS determined pre- and post-mitigation passage rates of sheep that crossed US Highway 93 were initially similar, they increased every year and were on average 217% higher following inclusion of wildlife crossings and by year 4 had ultimately increased 633% from pre-construction rates. Cameras recorded 6,936 crossings by a dozen wildlife species with sheep accounting for 95% of all crossings. Sheep used the 3 overpasses (90% of all sheep crossings) disproportionately more than the 3 culverts and 2 underpasses (10% of all sheep crossings) in the same area, and use of the 3 overpasses increased 905% in the first year. Sheep initially used the 30-m-wide overpasses at 83% and 175% higher passage rates than 2 15-m-wide structures; however, by year 4 passage rates were similar across overpasses. From February 2011 through February 2020, we documented 0.8 sheep–vehicle collisions/year for an overall 93.3% reduction from the 12 collisions per year previously documented. Most of the collisions occurred immediately following completion of the project and gradually reduced as sheep access points were identified and addressed through an adaptive mitigation process to iteratively improve success. Overpasses appear to be the preferred wildlife crossing type for sheep and when properly located and linked with ungulate exclusion fencing successfully reduced collisions and habitat fragmentation. These findings add to our knowledge base of effective roadway mitigation for different species. Long-term monitoring informs species learning curves, preference of wildlife crossing structure type, and adaptive mitigation opportunities to increase effectiveness of mitigation measures on current and future projects

    Evaluation of Right-of-Way Fence Tags to Reduce Animal-Vehicle Collisions

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    Animal-vehicle collisions (AVC) pose a serious and growing threat to motorists traveling on ADOT roads. Solutions exist to effectively mitigate AVC, such as wildlife crossing structures (overpasses and underpasses), however these solutions can be costly and untimely. Fence tags, a small reflective tag that is attached to the right-of-way fence and deter animals from crossing the fence, provide a potential cost-effective solution to reduce AVC. The research team evaluated the effectiveness of fence tags designed by Swift Creek, LLC, in reducing AVC. Fence tags were installed along both sides of five 2-mile segments of roadway and maintained for three years by replacing missing or damaged fence tags on a quarterly basis. The research team queried ADOT Crash Data to determine changes in AVC prior to the study (July 1, 2015 \u2013 June 30, 2018) and following fence tag installation (July 1, 2018 \u2013 June 30, 2021). Collisions in the areas where fence tags were installed were reduced by an average of 25.4 percent across all sites. This reduction was significant; however, the control sites were also reduced by a similar average of 25.8 percent across all study sites. These findings indicate that (1) the effectiveness of fence tags at reducing AVC were not noticeably different than the control, or (2) external factors that were not considered in the study, such as the effect of nearby road construction, may have influenced the effectiveness of the fence tags. To better understand the results of this study and improve available data for future projects and management decisions, the research team recommends: (1) further examining fence tags as a viable mitigation technique by looking at other aspects that could be taken into account in the study, such as other external factors affecting their use; measuring the effective tag size; implementing a longer observation period before, during, and after the intervention, etc. and (2) implementing data collection forms that capture animal type/species

    Consensus-based care recommendations for adults with myotonic dystrophy type 1

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    Purpose of review Myotonic dystrophy type 1 (DM1) is a severe, progressive genetic disease that affects between 1 in 3,000 and 8,000 individuals globally. No evidence-based guideline exists to inform the care of these patients, and most do not have access to multidisciplinary care centers staffed by experienced professionals, creating a clinical care deficit. Recent findings The Myotonic Dystrophy Foundation (MDF) recruited 66 international clinicians experienced in DM1 patient care to develop consensus-based care recommendations. MDF created a 2-step methodology for the project using elements of the Single Text Procedure and the Nominal Group Technique. The process generated a 4-page Quick Reference Guide and a comprehensive, 55-page document that provides clinical care recommendations for 19 discrete body systems and/or care considerations. Summary The resulting recommendations are intended to help standardize and elevate care for this patient population and reduce variability in clinical trial and study environments. Described as “one of the more variable diseases found in medicine,” myotonic dystrophy type 1 (DM1) is an autosomal dominant, triplet-repeat expansion disorder that affects somewhere between 1:3,000 and 1:8,000 individuals worldwide.1 There is a modest association between increased repeat expansion and disease severity, as evidenced by the average age of onset and overall morbidity of the condition. An expansion of over 35 repeats typically indicates an unstable and expanding mutation. An expansion of 50 repeats or higher is consistent with a diagnosis of DM1. DM1 is a multisystem and heterogeneous disease characterized by distal weakness, atrophy, and myotonia, as well as symptoms in the heart, brain, gastrointestinal tract, endocrine, and respiratory systems. Symptoms may occur at any age. The severity of the condition varies widely among affected individuals, even among members of the same family. Comprehensive evidence-based guidelines do not currently exist to guide the treatment of DM1 patients. As a result, the international patient community reports varied levels of care and care quality, and difficulty accessing care adequate to manage their symptoms, unless they have access to multidisciplinary neuromuscular clinics. Consensus-based care recommendations can help standardize and improve the quality of care received by DM1 patients and assist clinicians who may not be familiar with the significant variability, range of symptoms, and severity of the disease. Care recommendations can also improve the landscape for clinical trial success by eliminating some of the inconsistencies in patient care to allow more accurate understanding of the benefit of potential therapies

    Measurements of top-quark pair differential cross-sections in the eμe\mu channel in pppp collisions at s=13\sqrt{s} = 13 TeV using the ATLAS detector

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    Measurement of the W boson polarisation in ttˉt\bar{t} events from pp collisions at s\sqrt{s} = 8 TeV in the lepton + jets channel with ATLAS

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    Measurement of the bbb\overline{b} dijet cross section in pp collisions at s=7\sqrt{s} = 7 TeV with the ATLAS detector

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    Charged-particle distributions at low transverse momentum in s=13\sqrt{s} = 13 TeV pppp interactions measured with the ATLAS detector at the LHC

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