First Assessment of Mountains on Northwestern Ellesmere Island, Nunavut, as Potential Astronomical Observing Sites

Ellesmere Island, at the most northerly tip of Canada, possesses the highest mountain peaks within 10 degrees of the pole. The highest is 2616 m, with many summits over 1000 m, high enough to place them above a stable low-elevation thermal inversion that persists through winter darkness. Our group has studied four mountains along the northwestern coast which have the additional benefit of smooth onshore airflow from the ice-locked Arctic Ocean. We deployed small robotic site testing stations at three sites, the highest of which is over 1600 m and within 8 degrees of the pole. Basic weather and sky clarity data for over three years beginning in 2006 are presented here, and compared with available nearby sea-level data and one manned mid-elevation site. Our results point to coastal mountain sites experiencing good weather: low median wind speed, high clear-sky fraction and the expectation of excellent seeing. Some practical aspects of access to these remote locations and operation and maintenance of equipment there are also discussed.Comment: 21 pages, 2 tables, 15 figures; accepted for publication in PAS

Quality of life and BMI changes in youth participating in an integrated pediatric obesity treatment program

Background Changes in Quality of Life (QOL) measures over time with treatment of obesity have not previously been described for youth. We describe the changes from baseline through two follow up visits in youth QOL (assessed by the Pediatric Quality Life Inventory, PedsQL4.0), teen depression (assessed by the Patient Health Questionnaire, PHQ9A), Body Mass Index (BMI) and BMI z-score. We also report caregiver proxy ratings of youth QOL. Methods A sample of 267 pairs of youth and caregiver participants were recruited at their first visit to an outpatient weight-treatment clinic that provides care integrated between a physician, dietician, and mental health provider; of the 267, 113 attended a visit two (V2) follow-up appointment, and 48 attended visit three (V3). We investigated multiple factors longitudinally experienced by youth who are overweight and their caregivers across up to three different integrated care visits. We determined relationships at baseline in QOL, PHQ9A, and BMI z-score, as well as changes in variables over time using linear mixed models with time as a covariate. Results Overall across three visits the results indicate that youth had slight declines in relative BMI, significant increases in their QOL and improvements in depression. Conclusions We encourage clinicians and researchers to track youth longitudinally throughout treatment to investigate not only youth’s BMI changes, but also psychosocial changes including QOL

Music and Sound in Virtual/Augmented Realities—Questions, Challenges and Approaches

The mid-to-late 2010s saw a renewed interest in virtual reality technologies with the release of a wide selection of consumer VR headsets and glasses, and the increased power of smartphones to provide augmented reality experiences. While research on sound and music in these technologies has started to gather pace, practice and research continue to grapple with significant creative and practical questions. In addition, such discussions have tended to be limited within disciplinary or professional silos. The roundtable presented here was an effort to begin conversations across a variety of fields of research and practice. We shared perspectives and exchanged views informed by different disciplinary traditions and experiences. We also sought to identify key questions and issues regarding music and sound in VR/AR. Three main themes are presented here: 1) Spaces and musical performances, 2) Realities and realism, and 3) Movement, orientation, and disorientation

Modelling subject-specific childhood growth using linear mixed-effect models with cubic regression splines.

Childhood growth is a cornerstone of pediatric research. Statistical models need to consider individual trajectories to adequately describe growth outcomes. Specifically, well-defined longitudinal models are essential to characterize both population and subject-specific growth. Linear mixed-effect models with cubic regression splines can account for the nonlinearity of growth curves and provide reasonable estimators of population and subject-specific growth, velocity and acceleration.We provide a stepwise approach that builds from simple to complex models, and account for the intrinsic complexity of the data. We start with standard cubic splines regression models and build up to a model that includes subject-specific random intercepts and slopes and residual autocorrelation. We then compared cubic regression splines vis-à-vis linear piecewise splines, and with varying number of knots and positions. Statistical code is provided to ensure reproducibility and improve dissemination of methods. Models are applied to longitudinal height measurements in a cohort of 215 Peruvian children followed from birth until their fourth year of life.Unexplained variability, as measured by the variance of the regression model, was reduced from 7.34 when using ordinary least squares to 0.81 (p < 0.001) when using a linear mixed-effect models with random slopes and a first order continuous autoregressive error term. There was substantial heterogeneity in both the intercept (p < 0.001) and slopes (p < 0.001) of the individual growth trajectories. We also identified important serial correlation within the structure of the data (ρ = 0.66; 95 % CI 0.64 to 0.68; p < 0.001), which we modeled with a first order continuous autoregressive error term as evidenced by the variogram of the residuals and by a lack of association among residuals. The final model provides a parametric linear regression equation for both estimation and prediction of population- and individual-level growth in height. We show that cubic regression splines are superior to linear regression splines for the case of a small number of knots in both estimation and prediction with the full linear mixed effect model (AIC 19,352 vs. 19,598, respectively). While the regression parameters are more complex to interpret in the former, we argue that inference for any problem depends more on the estimated curve or differences in curves rather than the coefficients. Moreover, use of cubic regression splines provides biological meaningful growth velocity and acceleration curves despite increased complexity in coefficient interpretation.Through this stepwise approach, we provide a set of tools to model longitudinal childhood data for non-statisticians using linear mixed-effect models

Evidence of West Nile virus (WNV) circulation in wild birds and WNV RNA negativity in mosquitoes of the Danube Delta Biosphere Reserve, Romania, 2016

West Nile virus (WNV) is a zoonotic flavivirus whose transmission cycle in nature includes wild birds as amplifying hosts and ornithophilic mosquito vectors. Bridge vectors can transmit WNV to mammal species potentially causing West Nile Fever. Wild bird migration is a mode of WNV introduction into new areas. The Danube Delta Biosphere Reserve (DDBR) is a major stopover of wild birds migrating between Europe and Africa. The aim of this study was to investigate the presence of WNV in the DDBR during the 2016 transmission season in wild birds and mosquitoes. Blood from 68 wild birds (nine different species) trapped at four different locations was analyzed by competitive ELISA and Virus Neutralization Test (VNT), revealing positive results in 8/68 (11.8%) of the wild birds by ELISA of which six samples (three from juvenile birds) were confirmed seropositive by VNT. Mosquitoes (n = 6523, 5 genera) were trapped with CDC Mini Light traps at two locations and in one location resting mosquitoes were caught. The presence of WNV RNA was tested in 134 pools by reverse transcription quantitative PCR (RT-qPCR). None of the pools was positive for WNV-specific RNA. Based on the obtained results, WNV was circulating in the DDBR during 2016