102 research outputs found
Supplemental Material - Revisiting Analogical Reasoning in Computing Education: Use of Similarities Between Robot Programming Tasks in Debugging
No full textSupplemental Material for Revisiting Analogical Reasoning in Computing Education: Use of Similarities Between Robot Programming Tasks in Debugging by ChanMin Kim, Emre Dinç, Eunseo Lee, Afaf Baabdullah, Anna Y. Zhang, and Brian R. Belland in Journal of Educational Computing Research</p
History of gestational diabetes and incident nonalcoholic fatty liver disease: the Kangbuk Samsung Health Study
No full textINTRODUCTION: We examined the relationship between a previous history of gestational diabetes mellitus (pGDM) and risk of incident nonalcoholic fatty liver disease (NAFLD) and investigated the effect of insulin resistance or development of diabetes as mediators of any association. METHODS: We performed a retrospective cohort study of 64,397 Korean parous women without NAFLD. The presence of and the severity of NAFLD at baseline and follow-up were assessed using liver ultrasonography. Cox proportional hazards models were used to determine adjusted hazard ratios for incident NAFLD according to a self-reported GDM history, adjusting for confounders as time-dependent variables. Mediation analyses were performed to examine whether diabetes or insulin resistance may mediate the association between pGDM and incident NAFLD. RESULTS: During a median follow-up of 3.7 years, 6,032 women developed incident NAFLD (of whom 343 had moderate-to-severe NAFLD). Multivariable adjusted hazard ratios (95% confidence intervals) comparing women with time-dependent pGDM with the reference group (no pGDM) were 1.46 (1.33-1.59) and 1.75 (1.25-2.44) for incident overall NAFLD and moderate-to-severe NAFLD, respectively. These associations remained significant in analyses restricted to women with normal fasting glucose <100 mg/dL or that excluded women with prevalent diabetes at baseline or incident diabetes during follow-up. Diabetes and insulin resistance (Homeostatic Model Assessment for Insulin Resistance) each mediated <10% of the association between pGDM and overall NAFLD development. DISCUSSION: A previous history of GDM is an independent risk factor for NAFLD development. Insulin resistance, measured by the Homeostatic Model Assessment for Insulin Resistance, and development of diabetes each explained only <10% of the association between GDM and incident NAFLD.</p
Serum 25-hydroxyvitamin D levels and risk of colorectal cancer: an age-stratified analysis
No full textBackground and aims: the role of circulating 25-hydroxyvitamin D (25(OH)D) in prevention of early-onset colorectal cancer (CRC) in young adults under 50 years is uncertain. We evaluated the age-stratified associations (<50 vs. ≥50 years) :circulating 25(OH)D levels and the risk of CRC in a large sample of Korean adults.Methods: our cohort study included 236,382 participants (mean [standard deviation] age, 38.0 [9.0] years) who underwent a comprehensive health examination, including measurement of serum 25(OH)D levels. Serum 25(OH)D levels were categorized as follows: <10, 10–20, and ≥20 ng/mL. CRC, along with the histologic subtype, site, and invasiveness was ascertained through linkage with the national cancer registry. Cox proportional hazard models were used to estimate hazard ratios (HRs; 95% confidence intervals [CIs]) for incident CRC according to the serum 25(OH)D status, with adjustment for potential confounders.Results: during the 1,393,741 person-years of follow-up (median, 6.5 years; interquartile range, 4.5–7.5 years), 341 participants developed CRC (incidence rate, 19.2 per 105 person-years). Among young individuals aged <50 years, serum 25(OH)D levels were inversely associated with the risk of incident CRC with HRs (95% CIs) of 0.61 (0.43–0.86) and 0.41 (0.27–0.63) for 25(OH)D 10-19 and ≥20 ng/mL, respectively, with respect to the reference (<10 ng/mL) (p for trend <0.001, time-dependent model). Significant associations were evident for adenocarcinoma, colon cancer, and invasive cancers. For those aged ≥50 years, associations were similar, although slightly attenuated compared to younger individuals. Conclusions: serum 25(OH)D levels may have beneficial associations with the risk of developing CRC for both early-onset and late-onset disease. <br/
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Methods for Estimating the Health Effects of Exposure to Point Sources of Emissions Using Large-Scale and Diverse Data Sources
No full textThere is a well-documented association between exposure to fine particulate matter (PM2.5) and numerous health outcomes, with some evidence suggesting PM2.5 originating from coal combustion may have different health impacts. These studies typically estimate exposure to coal-derived PM2.5 based on the presence of certain chemical tracers measured in the air near exposed populations. Interpreting such user-defined source profiles requires a certain degree of subjectivity and approximation, and such approaches do not consider the contributions of individual coal power plants. This limits their relevance for informing air quality management interventions that must, ultimately, be implemented at individual sources (e.g., through scrubber installation, closing inefficient plants, etc.). Existing literature that does focus on specific point sources uses computationally expensive models for pollution transport, thus limiting their applicability to only a few power plants or groups of power plants.
In chapter one, we employ a recently-developed, reduced-complexity air quality model to provide the first national study of the association between long-term exposure to emissions from individual coal power plants and Ischemic Heart Disease hospitalization. The study provides a novel combination of observed data, statistical methods, and tools from environmental engineering. Rooting the approach to causal inference methods to isolate the coal emissions/health relationship represents an important step towards establishing the causal links between emissions and health necessary to drive policy changes.
In chapter two, we provide the first investigation of whether a purely statistical, data-driven approach to source-receptor mapping can reproduce knowledge typically produced by complex chemical transport models. The ability to do so would provide a more computationally nimble approach to estimate S-R relationships in a wider variety of settings. Specifically, we consider daily sulfur dioxide (SO2) emissions from 385 coal-fired power plants operating in the U.S. in 2005, and estimate a source-receptor mapping to 732 EPA Air Quality System (AQS) monitor locations measuring daily fine particulate matter (PM2.5). Results were framed as an ``emissions network'' -- power plants and monitors are nodes and significant associations between their daily time-series define edges in the network -- representing an annual pattern in coal emissions transport for 2005. The results of the proposed approach were shown to hold some promise in capturing general patterns of pollution transport and source-specific exposures, but was limited in its ability to recover individual source-receptor links relative to a recently proposed reduced complexity CTM. Our investigation uncovered several statistical challenges for which we provide initial progress towards addressing, with future refinements holding promise for improving the fidelity of the purely statistical approach.
In chapter three, we explore the value of the statistical, data-driven approach to source-receptor mapping to evaluate how source-receptor relationships vary over time. Specifically, we use the statistical methods to explore seasonal variability (winter, spring, summer, and fall) in coal emissions transport using daily SO2 emissions from coal-fired power plants operating in the United States from 2005-2010 and daily PM2.5 concentrations at air quality monitors. We fit four emissions networks per year (one each season) from 2005-2010 and compared them across seasons and years at various levels of granularity. Our results point to important short-term variability in source-receptor mappings that may not be captured in annual models.Biostatisticsair pollution health effects; PM2.5; source-oriented; coal combustion; source-receptor mapping; reduced complexity air quality model
Email, Self-Regulation, Self-Efficacy, and Achievement in a College Online Mathematics Course
No full textThe purpose of this study was to: (a) investigate the effects of email to enhance learners\u27 use of self-regulation strategies; (b) examine different effects between email list and individually addressed notes on the enhancement of self-regulation; (c) observe and record changes in self-regulation and self-efficacy; and (d) explore the relationships among self-regulation, self-efficacy, and achievement. For an entire semester, 103 college students enrolled in an online, asynchronous mathematics course participated in this study. They were randomly assigned to one of three groups. The first group received self-regulation strategies without personalized messages; the second group received self-regulation strategies with personalized messages; and the third group received neither self-regulation strategies nor personalized messages. Results indicated that there was no statistically significant effect for the email treatments but a statistically significant relationship was observed between self-efficacy and achievement. The findings are discussed with an emphasis on the reciprocal relations between self-efficacy and self-regulation
Effects of an Emotion Control Treatment on Academic Emotions, Motivation and Achievement in an Online Mathematics Course
No full textWe designed and developed an emotion control treatment and investigated its effects on college students’ academic emotions, motivation, and achievement in an online remedial mathematics course. The treatment group showed more positive emotions of enjoyment and pride than the control group. The treatment group also showed a higher level of motivation than the control group but there was no difference between the two groups in achievement. Implications for the design and development of interventions or systems for students’ emotion control are discussed
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