Discovering the Data of Safety: Embry-Riddle’s Aviation Safety and Security Archives

The path to the sky and beyond has not been simple or obstacle-free, but dedicated dreamers have worked to overcome obstacles, learn from mishaps, and develop new technologies to achieve their goals. As the leading university for aviation and aerospace education, Embry-Riddle Aeronautical University maintains a firm commitment to the practice and study of safety. As part of this mission, the university has established the Aviation Safety and Security Archives (ASASA) which is a national treasure of aviation safety history and information

A quantitative review of abundance‐based species distribution models

The contributions of species to ecosystem functions or services depend not only on their presence but also on their local abundance. Progress in predictive spatial modelling has largely focused on species occurrence rather than abundance. As such, limited guidance exists on the most reliable methods to explain and predict spatial variation in abundance. We analysed the performance of 68 abundance-based species distribution models fitted to 800 000 standardised abundance records for more than 800 terrestrial bird and reef fish species. We found a large amount of variation in the performance of abundance-based models. While many models performed poorly, a subset of models consistently reconstructed range-wide abundance patterns. The best predictions were obtained using random forests for frequently encountered and abundant species and for predictions within the same environmental domain as model calibration. Extending predictions of species abundance outside of the environmental conditions used in model training generated poor predictions. Thus, interpolation of abundances between observations can help improve understanding of spatial abundance patterns, but our results indicate extrapolated predictions of abundance under changing climate have a much greater uncertainty. Our synthesis provides a road map for modelling abundance patterns, a key property of species distributions that underpins theoretical and applied questions in ecology and conservation

Effect of Menstrual Cycle and Hormonal Contraception on Musculoskeletal Health and Performance: Protocol for a Prospective Cohort Design and Cross-Sectional Comparison

Background Women of reproductive age experience cyclical variation in the female sex steroid hormones 17β-estradiol and progesterone during the menstrual cycle that is attenuated by some hormonal contraceptives. Estrogens perform a primary function in sexual development and reproduction but have nonreproductive effects on bone, muscle, and sinew tissues (ie, ligaments and tendons), which may influence injury risk and physical performance. Objective The purpose of the study is to understand the effect of the menstrual cycle and hormonal contraceptive use on bone and calcium metabolism, and musculoskeletal health and performance. Methods A total of 5 cohorts of physically active women (aged 18-40 years) will be recruited to participate: eumenorrheic, nonhormonal contraceptive users (n=20); combined oral contraceptive pill (COCP) users (n=20); hormonal implant users (n=20); hormonal intrauterine system users (n=20); and hormonal injection users (n=20). Participants must have been using the COCP and implant for at least 1 year and the intrauterine system and injection for at least 2 years. First-void urine samples and fasted blood samples will be collected for biochemical analysis of calcium and bone metabolism, hormones, and metabolic markers. Knee extensor and flexor strength will be measured using an isometric dynamometer, and lower limb tendon and stiffness, tone, and elasticity will be measured using a Myoton device. Functional movement will be assessed using a single-leg drop to assess the frontal plane projection angle and the qualitative assessment of single leg loading. Bone density and macro- and microstructure will be measured using ultrasound, dual-energy x-ray absorptiometry, and high-resolution peripheral quantitative computed tomography. Skeletal material properties will be estimated from reference point indentation, performed on the flat surface of the medial tibia diaphysis. Body composition will be assessed by dual-energy x-ray absorptiometry. The differences in outcome measures between the hormonal contraceptive groups will be analyzed in a one-way between-group analysis of covariance. Within the eumenorrheic group, the influence of the menstrual cycle on outcome measures will be assessed using a linear mixed effects model. Within the COCP group, differences across 2 time points will be analyzed using the paired-samples 2-tailed t test. Results The research was funded in January 2020, and data collection started in January 2022, with a projected data collection completion date of August 2024. The number of participants who have consented at the point of manuscript submission is 66. It is expected that all data analysis will be completed and results published by the end of 2024. Conclusions Understanding the effects of the menstrual cycle and hormonal contraception on musculoskeletal health and performance will inform contraceptive choices for physically active women to manage injury risk

Effect of menstrual cycle and hormonal contraception on musculoskeletal health and performance: A prospective cohort design and cross-sectional comparison

Background: Women of reproductive age experience cyclical variation in the female sex steroid hormones, 17β-oestradiol and progesterone, during the menstrual cycle that are attenuated by some hormonal contraceptives. Oestrogens perform a primary function in sexual development and reproduction, but have non-reproductive effects on bone, muscle, and sinew tissues (i.e., ligaments and tendons), which may influence injury risk and physical performance. Objectives: The purpose of the study is to understand the effect of the menstrual cycle and hormonal contraceptive use on bone and calcium metabolism, and musculoskeletal health and performance. Methods: Five cohorts of physically active women (aged 18-40 years) will be recruited to participate: eumenorrheic, non-hormonal contraceptive users (EUM; n=20), combined oral contraceptive pill users (COCP; n=20); hormonal implant users (n=20); hormonal intra-uterine system users (IUS; n=20); and hormonal injection users (n=20). Participants must have been using the COCP and Implant for at least 1 year and the IUS and Injection for at least 2 years. First void urine samples and fasted blood samples will be collected for biochemical analysis of calcium and bone metabolism, hormones, and metabolic markers. Knee extensor and flexor strength will be measured using an isometric dynamometer, and lower limb tendon and stiffness, tone and elasticity will be measured using a Myoton device. Functional movement will be assessed using a single leg drop to assess frontal plane projection angle and the qualitative assessment of single leg loading. Bone density and macro- and microstructure will be measured using ultrasound, DXA, and HRpQCT. Skeletal material properties will be estimated from Reference Point Indentation, performed on the flat surface of the medial tibia diaphysis. Body composition will be assessed by DXA. The differences in outcome measures between the hormonal contraceptive groups will be analysed in a one-way between group ANCOVA. Within the EUM group, the influence of the menstrual cycle on outcome measures will be assessed using linear mixed effects model. Within the COCP, differences across two time points will be analysed using paired samples t-test. Results: The research was funded in January 2020 and data collection started in January 2022, with a projected data collection completion date of August 2024. The number of participants that have consented at the point of manuscript submission is 66. It is expected that all data analysis will be completed, and results published by the end of 2024. Conclusions: Understanding the effects of the menstrual cycle and hormonal contraception on musculoskeletal health and performance will inform contraceptive choices for physically active women to manage injury risk

BioTIME:a database of biodiversity time series for the Anthropocene

Abstract Motivation: The BioTIME database contains raw data on species identities and abundances in ecological assemblages through time. These data enable users to calculate temporal trends in biodiversity within and amongst assemblages using a broad range of metrics. BioTIME is being developed as a community‐led open‐source database of biodiversity time series. Our goal is to accelerate and facilitate quantitative analysis of temporal patterns of biodiversity in the Anthropocene. Main types of variables included: The database contains 8,777,413 species abundance records, from assemblages consistently sampled for a minimum of 2 years, which need not necessarily be consecutive. In addition, the database contains metadata relating to sampling methodology and contextual information about each record. Spatial location and grain: BioTIME is a global database of 547,161 unique sampling locations spanning the marine, freshwater and terrestrial realms. Grain size varies across datasets from 0.0000000158 km² (158 cm²) to 100 km² (1,000,000,000,000 cm²). Time period and grain: BioTIME records span from 1874 to 2016. The minimal temporal grain across all datasets in BioTIME is a year. Major taxa and level of measurement: BioTIME includes data from 44,440 species across the plant and animal kingdoms, ranging from plants, plankton and terrestrial invertebrates to small and large vertebrates. Software format: .csv and .SQL

BioTIME:a database of biodiversity time series for the Anthropocene

Motivation: The BioTIME database contains raw data on species identities and abundances in ecological assemblages through time. These data enable users to calculate temporal trends in biodiversity within and amongst assemblages using a broad range of metrics. BioTIME is being developed as a community led open-source database of biodiversity time series. Our goal is to accelerate and facilitate quantitative analysis of temporal patterns of biodiversity in the Anthropocene.Main types of variables included: The database contains 8,777,413 species abundance records, from assemblages consistently sampled for a minimum of two, which need not necessarily be consecutive. In addition, the database contains metadata relating to sampling methodology andcontextual information about each record.Spatial location and grain: BioTIME is a global database of 547,161 unique sampling locations spanning the marine, freshwater and terrestrial realms. Grain size varies across datasets from 0.0000000158 km2 (158 cm2) to 100 km2 (1 000 000 000 000 cm2).Time period and grain: BioTIME records span from 1874 to 2016. The minimum temporal grain across all datasets in BioTIME is year.Major taxa and level of measurement: BioTIME includes data from 44,440 species across the plant and animal kingdoms, ranging from plants, plankton, and terrestrial invertebrates to small and large vertebrates.Software format: .csv and .SQ