Editor\u27s Introduction and Acknowledgments

An introduction to the journal Research in Outdoor Education, volume 7 is presented by the authors on behalf of the Coalition for Education in the Outdoors (CEO) Research Committee

Promoting Bicycle Commuter Safety, Research Report 11-08

We present an overview of the risks associated with cycling to emphasize the need for safety. We focus on the application of frameworks from social psychology to education, one of the 5 Es—engineering, education, enforcement, encouragement, and evaluation. We use the structure of the 5 Es to organize information with particular attention to engineering and education in the literature review. Engineering is essential because the infrastructure is vital to protecting cyclists. Education is emphasized since the central focus of the report is safety

High-risk and multiple human papillomavirus (HPV) infections in cancer-free Jamaican women

<p>Abstract</p> <p>Background</p> <p>Vaccines, that target human papillomavirus (HPV) high risk genotypes 16 and 18, have recently been developed. This study was aimed at determining genotypes commonly found in high-risk and multiple-HPV infections in Jamaican women. Two hundred and fifty three (253) women were enrolled in the study. Of these, 120 pregnant women, aged 15–44 years, were recruited from the Ante Natal Clinic at the University Hospital of the West Indies and 116 non-pregnant, aged 19–83, from a family practice in Western Jamaica. Cervical cell samples were collected from the women and HPV DNA was detected using Polymerase Chain Reaction and Reverse Line Hybridization. HPV genotypes were assessed in 236 women. Data were collected from January 2003 to October 2006.</p> <p>Results</p> <p>HPV DNA was detected in 87.7% (207/236) and of these 80.2% were positive for high-risk types. The most common high-risk HPV types were: HPV 45 (21.7%), HPV 58 (18.8%), HPV 16 (18.4%), HPV 35 (15.0%), HPV 18 (14.5%), HPV 52 (12.0%) and HPV 51(11.1%). Other high-risk types were present in frequencies of 1.4% – 7.2%.</p> <p>Multivariate regression analyses showed that bacterial vaginosis predicted the presence of multiple infections (OR 3.51; CI, 1.26–9.82) and that alcohol use (OR 0.31; CI, 0.15–0.85) and age at first sexual encounter (12–15 years: OR 3.56; CI, 1.41–9.12; 16–19 years, OR 3.53, CI, 1.22–10.23) were significantly associated with high risk infections. Cervical cytology was normal in the majority of women despite the presence of high-risk and multiple infections.</p> <p>Conclusion</p> <p>HPV genotype distribution in this group of Jamaican women differs from the patterns found in Europe, North America and some parts of Asia. It may be necessary therefore to consider development of other vaccines which target genotypes found in our and similar populations. HPV genotyping as well as Pap smears should be considered.</p

Integrating Remote Sensing with Ground-based Observations to Quantify the Effects of an Extreme Freeze Event on Black Mangroves (Avicennia germinans) at the Landscape Scale

Climate change is altering the frequency and intensity of extreme weather events. Quantifying ecosystem responses to extreme events at the landscape scale is critical for understanding and responding to climate-driven change but is constrained by limited data availability. Here, we integrated remote sensing with ground-based observations to quantify landscape-scale vegetation damage from an extreme climatic event. We used ground- and satellite-based black mangrove (Avicennia germinans) leaf damage data from the northern Gulf of Mexico (USA and Mexico) to examine the effects of an extreme freeze in a region where black mangroves are expanding their range. The February 2021 event produced coastal temperatures as low as − 10 °C in some areas, exceeding thresholds for A. germinans damage and mortality. We used Sentinel-2 surface reflectance data to assess vegetation greenness before and after the freeze, along with ground-based observations of A. germinans leaf damage. Our results show a negative, nonlinear threshold relationship between A. germinans leaf damage and minimum temperature, with a temperature threshold for leaf damage near − 6 °C. Satellite-based analyses indicate that, at the landscape scale, damage was particularly severe along the central Texas coast, where the freeze event affected \u3e 2000 ha of A. germinans-dominated coastal wetlands. Our analyses highlight the value of pairing remotely sensed data with regional, ground-based observations for quantifying and extrapolating the effects of extreme freeze events on mangroves and other tropical, cold-sensitive plants. The results also demonstrate how extreme freeze events govern the expansion and contraction of mangroves near northern range limits in North America

VarSight: prioritizing clinically reported variants with binary classification algorithms.

BackgroundWhen applying genomic medicine to a rare disease patient, the primary goal is to identify one or more genomic variants that may explain the patient's phenotypes. Typically, this is done through annotation, filtering, and then prioritization of variants for manual curation. However, prioritization of variants in rare disease patients remains a challenging task due to the high degree of variability in phenotype presentation and molecular source of disease. Thus, methods that can identify and/or prioritize variants to be clinically reported in the presence of such variability are of critical importance.MethodsWe tested the application of classification algorithms that ingest variant annotations along with phenotype information for predicting whether a variant will ultimately be clinically reported and returned to a patient. To test the classifiers, we performed a retrospective study on variants that were clinically reported to 237 patients in the Undiagnosed Diseases Network.ResultsWe treated the classifiers as variant prioritization systems and compared them to four variant prioritization algorithms and two single-measure controls. We showed that the trained classifiers outperformed all other tested methods with the best classifiers ranking 72% of all reported variants and 94% of reported pathogenic variants in the top 20.ConclusionsWe demonstrated how freely available binary classification algorithms can be used to prioritize variants even in the presence of real-world variability. Furthermore, these classifiers outperformed all other tested methods, suggesting that they may be well suited for working with real rare disease patient datasets

Backward Nonlinear Smoothing Diffusions

We present a backward diffusion flow (i.e. a backward-in-time stochastic differential equation) whose marginal distribution at any (earlier) time is equal to the smoothing distribution when the terminal state (at a latter time) is distributed according to the filtering distribution. This is a novel interpretation of the smoothing solution in terms of a nonlinear diffusion (stochastic) flow. This solution contrasts with, and complements, the (backward) deterministic flow of probability distributions (viz. a type of Kushner smoothing equation) studied in a number of prior works. A number of corollaries of our main result are given including a derivation of the time-reversal of a stochastic differential equation, and an immediate derivation of the classical Rauch-Tung-Striebel smoothing equations in the linear setting

The Iowa Homemaker vol.32, no.8

Our Political Door Ajar, Dorothy Will, page 7 Parisian Views, Jane Steele, page 8 Warning! To a GI Wife Abroad, Roger Blobaum, page 9 Interviews – Give and Take, Nancy Butler, page 10 Veishea Highlight – Home Economics, Jane Brintlinger, page 11 Knowledge with Fun, Mary Camille Grout, page 14 New Collegiate You, Carol Dee Legg, page 15 What’s New, Evelyn Toulouse and Dorothy Will, page 16 Trends, Ruth Anderson, page 2

Investigation of Rural Roadway Departures

228411Roadway fatalities are a major priority in the transportation sector. UDOT has noted that fatalities increased in 2020 with the leading cause, by a substantial margin, being rural roadway departures. Knowledge about the specific characteristics of rural roadway departure crashes can help UDOT to develop proper mitigation strategies. This research was performed with the goal of investigating temporal and spatial characteristics associated with rural roadway departure fatalities and other crashes to identify action steps to reduce roadway departure fatalities. Study into potential methods of reducing crashes was performed to answer the following questions: Where do these crashes occur? When are roadway departures most common? What are the primary contributing factors? The identified answers to these questions will help develop methods of working through public outreach, education, engineering, and design to reduce rural roadway departure crashes and provide reference for future research and development. Through this research, patterns relating to the occurrence of these roadway departures that can be used to mitigate problems in the future were identified and highlighted. Key factors include high-risk behaviors such as drowsy driving, DUI and wrong-way driving, barriers, shoulder width, etc

Ensuring that COVID-19 research is inclusive: guidance from the NIHR INCLUDE project

Objective: To provide guidance to researchers, funders, regulators and study delivery teams to ensure that research on COVID-19 is inclusive, particularly of groups disproportionately affected by COVID-19 and who may have been historically under-served by research. Summary of key points: Groups who are disproportionately affected by COVID-19 include (but are not limited to) older people, people with multiple long-term conditions, people with disabilities, people from Black, Asian and Ethnic minority groups, people living with obesity, people who are socioeconomically deprived and people living in care homes. All these groups are under-served by clinical research, and there is an urgent need to rectify this if COVID-19 research is to deliver relevant evidence for these groups who are most in need. We provide a framework and checklists for addressing key issues when designing and delivering inclusive COVID-19 research, based on the National Institute for Health Research INnovations in CLinical trial design and delivery for the UnDEr-served project roadmap. Strong community engagement, codevelopment and prioritisation of research questions and interventions are essential. Under-served groups should be represented on funding panels and ethics committees, who should insist on the removal of barriers to participation. Exclusion criteria should be kept to a minimum; intervention delivery and outcome measurement should be simple, flexible and tailored to the needs of different groups, and local advice on the best way to reach and engage with under-served communities should be taken by study delivery teams. Data on characteristics that allow identification of under-served groups must be collected, analyses should include these data to enable subgroup comparisons and results should be shared with under-served groups at an early stage. Conclusion: Inclusive COVID-19 research is a necessity, not a luxury, if research is to benefit all the communities it seeks to serve. It requires close engagement with under-served groups and attention to aspects of study topic, design, delivery, analysis and dissemination across the research life cycle