Many individuals, including dementia caregivers, use blogs to share their experiences. These blogs contain rich narratives representing an untapped resource for understanding the psychosocial impact of caring for a person with dementia at the family level. The present study used blogs written by caregivers of persons with dementia to explore how these individuals leveraged this medium as part of the caregiving experience. Blogs written by self-identified informal caregivers of persons with dementia were identified using a systematic search method, and data were analyzed using a qualitative thematic analysis. Four themes emerged from the narratives: social support through communication and engagement, information gathering and seeking, reminiscing and legacy building, and altruism. By understanding the ways in which individuals providing care for persons with dementia use social media as part of the caregiving experience, family nurses can develop interventions and services aimed at improving caregiver burden and quality of life.

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Increasingly, natural history museum collections are being used to generate large‐scale morphological datasets to address a range of macroecological and macroevolutionary questions. One challenge to this approach is that large numbers of individuals either from a single species or from taxonomically broad sets of species may be necessary to characterize morphology at the relevant spatial, phylogenetic or temporal scales. We present ‘Skelevision’, a method for rapidly handling, photographing and measuring skeletal specimens with a computer vision approach that uses a deep neural network to segment the photographs of specimens into individual bones, and identify and measure functional aspects of those bones. We demonstrate the scale of what is feasible with Skelevision by estimating 11 functional traits from 11 different bones for 12,450 bird skeletal specimens spanning 1,882 species of passerines (~32% of all passerine diversity). We quantify the accuracy of Skelevision estimates by comparing them to handmade measurements for 174 specimens from 115 species across 79 genera that span 59 families. Skelevision is precise, with a mean standard deviation of 0.86 mm for repeated independent measurements of individual bones, and is extremely accurate, with a mean RMSE of 0.89 mm across all traits when compared to handmade measurements. There is minimal phylogenetic signal in the measurement error (mean Pagel's λ across traits = 0.13), and Skelevision estimates are robust to variation in the degree to which specimens remain articulated. This approach has several important advantages over traditional methods for building large‐scale morphological datasets (e.g. measurements from long‐term field‐based operations or handmade measurements of museum specimens). First, measuring new specimens only requires the collection of photographs, which can then be measured automatically, and effectively instantaneously, with the neural network. This is a significant departure from the time and skill required to measure skeletal specimens by hand. Second, the measurements are repeatable. Third, even as the dataset of photographed specimens expands, the amount of annotation data needed to measure new traits on all of the photographed specimens using the neural network will remain fixed and can be done without re‐capturing images.

The role of powered two-wheeler (PTW) transport from the perspective of a more sustainable mobility system is undermined by the associated high injury risk due to crashes. Motorcycle-based active safety systems promise to avoid or mitigate many of these crashes suffered by PTW riders. Despite this, most systems are still only in the prototype phase and understanding which systems have the greatest chance of reducing crashes is an important step in prioritizing their development. Earlier studies have examined the applicability of these systems to individual crash configurations, e.g., rear-end vs. intersection crashes. However, there may be large regional differences in the distribution of PTW crash configurations, motorcycle types, and road systems, and hence in the priority for the development of systems. The study objective is to compare the applicability of five active safety systems for PTWs in Australia, Italy, and the US using real-world crash data from each region. The analysis found stark differences in the expected applicability of the systems across the three regions. ABS generally resulted in the most applicable system, with estimated applicability in 45–60% of all crashes. In contrast, in 20–30% of the crashes in each country, none of the safety systems analyzed were found to be applicable. This has important implications for manufacturers and researchers, but also for regulators, which may demand country-specific minimum performance requirements for PTW active safety countermeasures.

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