Using Eye-Tracking and Molecular Modeling to Explore Students’ Strategies for Solving Organic Stereochemical Problems

Stereochemistry concepts are often some of the most difficult topics for students to grasp in the organic chemistry curriculum. Several factors may influence students’ abilities to solve stereochemistry problems, including their spatial abilities, strategy choice, and ability to use various types of spatial representations. A mixed-method study was conducted to investigate the role that these factors play when novice organic chemistry students solve stereochemistry problems. Eye-tracking methods were used in an attempt to capture cognitive processes of students while solving these problems. Additionally, three-dimensional molecular models and spatial ability measures were used to further analyze and characterize their strategies for solving these problems. Quantitative eye-tracking data revealed key insights into how organic chemistry students solve stereochemistry problems. Further, qualitative data indicated that strategy choice and representation type impact success on stereochemistry problems. Finally, results showed a significant relationship between spatial ability and performance in a first semester organic chemistry course. The findings of this study have several implications for how we teach chemistry. First, students who struggle with visuospatial tasks due to their inability to successfully apply holistic mental rotation strategies may benefit when they are taught to use analytic strategies. However, while analytic strategies may help students to arrive at the correct answer on stereochemical problems, they may do little to help students visualize the three-dimensional arrangement of atoms or the spatial relationships between molecules. Additionally, performance on stereochemical problems may be enhanced when students are allowed to use physical models, and when they are encouraged to search for key features of the molecule during the problem-solving process

Percussion Convocation

List of performers and performances

Incidence of Symptomatic Vertebral Fractures Among Newly Diagnosed Autoimmune Diseases Initiating Glucocorticoid Therapy

Few data are available regarding vertebral fracture risk in patients treated with corticosteroids including patients with interstitial lung disease (ILD). The aim of the present study was to identify risk factors for symptomatic vertebral fracture analyzed in patients with newly diagnosed autoimmune diseases. This was an observational cohort study conducted in the National Hospital Organization-EBM study group from 2006 to 2008. The study subjects were autoimmune disease patients who were newly treated with glucocorticoids (GCs). The primary endpoint was the first occurrence of vertebral fracture diagnosed by x-rays. Cox proportional-hazards regression was used to determine independent risk factors for vertebral fracture with covariates including sex, age, comorbidity, laboratory data, use of immunosuppressants, and dose of GCs. Survival was analyzed according to the Kaplan-Meier method and assessed by the log-rank test. Among 604 patients of mean age 59.5 years and mean GC dose 50.4mg/d (first 1 months), 19 patient (3.1%) had at least 1 symptomatic vertebral fracture during 1.9 years of follow-up period. Cox regression model demonstrated that the relative risk for symptomatic vertebral fracture was independently higher in patient with ILD (hazard ratio [HR]=2.86, 95% confidence interval [CI]=1.10-7.42, P=0.031) and in every 10-year increment of the age of disease onset (HR=1.57, 95% CI=1.09-2.26, P=0.015). Kaplan-Meier analyses demonstrated that the incidence of vertebral fractures in patients with ILD was significantly higher in comparison with those without ILD. Our results indicate a higher risk of vertebral facture in patients with ILD and elderly patients during the initial GC treatment against autoimmune diseases. There is a need for further, even longer-term, prospective studies subjected patients with autoimmune disease, including ILD, under GC treatment

The Lantern, 2014-2015

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An empirical evaluation of camera trap study design: How many, how long and when?

Abstract Camera traps deployed in grids or stratified random designs are a well‐established survey tool for wildlife but there has been little evaluation of study design parameters. We used an empirical subsampling approach involving 2,225 camera deployments run at 41 study areas around the world to evaluate three aspects of camera trap study design (number of sites, duration and season of sampling) and their influence on the estimation of three ecological metrics (species richness, occupancy and detection rate) for mammals. We found that 25–35 camera sites were needed for precise estimates of species richness, depending on scale of the study. The precision of species‐level estimates of occupancy (ψ) was highly sensitive to occupancy level, with 0.75) species, but more than 150 camera sites likely needed for rare (ψ < 0.25) species. Species detection rates were more difficult to estimate precisely at the grid level due to spatial heterogeneity, presumably driven by unaccounted habitat variability factors within the study area. Running a camera at a site for 2 weeks was most efficient for detecting new species, but 3–4 weeks were needed for precise estimates of local detection rate, with no gains in precision observed after 1 month. Metrics for all mammal communities were sensitive to seasonality, with 37%–50% of the species at the sites we examined fluctuating significantly in their occupancy or detection rates over the year. This effect was more pronounced in temperate sites, where seasonally sensitive species varied in relative abundance by an average factor of 4–5, and some species were completely absent in one season due to hibernation or migration. We recommend the following guidelines to efficiently obtain precise estimates of species richness, occupancy and detection rates with camera trap arrays: run each camera for 3–5 weeks across 40–60 sites per array. We recommend comparisons of detection rates be model based and include local covariates to help account for small‐scale variation. Furthermore, comparisons across study areas or times must account for seasonality, which could have strong impacts on mammal communities in both tropical and temperate sites

The Lantern, 2011-2012

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SNAPSHOT USA 2019 : a coordinated national camera trap survey of the United States

This article is protected by copyright. All rights reserved.With the accelerating pace of global change, it is imperative that we obtain rapid inventories of the status and distribution of wildlife for ecological inferences and conservation planning. To address this challenge, we launched the SNAPSHOT USA project, a collaborative survey of terrestrial wildlife populations using camera traps across the United States. For our first annual survey, we compiled data across all 50 states during a 14-week period (17 August - 24 November of 2019). We sampled wildlife at 1509 camera trap sites from 110 camera trap arrays covering 12 different ecoregions across four development zones. This effort resulted in 166,036 unique detections of 83 species of mammals and 17 species of birds. All images were processed through the Smithsonian's eMammal camera trap data repository and included an expert review phase to ensure taxonomic accuracy of data, resulting in each picture being reviewed at least twice. The results represent a timely and standardized camera trap survey of the USA. All of the 2019 survey data are made available herein. We are currently repeating surveys in fall 2020, opening up the opportunity to other institutions and cooperators to expand coverage of all the urban-wild gradients and ecophysiographic regions of the country. Future data will be available as the database is updated at eMammal.si.edu/snapshot-usa, as well as future data paper submissions. These data will be useful for local and macroecological research including the examination of community assembly, effects of environmental and anthropogenic landscape variables, effects of fragmentation and extinction debt dynamics, as well as species-specific population dynamics and conservation action plans. There are no copyright restrictions; please cite this paper when using the data for publication.Publisher PDFPeer reviewe