429 research outputs found

    Warning Times and Impact Predictions of Asteroids and Comets on a Collision Course with Earth

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    This study investigates the amount of data and time necessary to accurately predict Earth impacts of Earth Crossing Objects (ECOs). Trajectories are simulated by numerically integrating in an N-Body system. Given final impact parameters, the trajectory is propagated backwards to an earlier time, creating initial conditions and simulated observation data at requested intervals to which Gaussian random noise is introduced. Utilizing a Bayes Filter to estimate position and velocity from the simulated observation data, the estimate is then propagated forward in time to determine whether or not an impact can be accurately predicted. State vectors and covariance matrices are then propagated to the impact time and the one sigma error ellipsoid is analyzed

    The long-term impact of rail abandonment on manufacturing in Arkansas

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    Despite the fact that railroads are an important part of the U.S. economy, the number of rail carriers and miles of rail lines have been declining. The resulting lack of transportation alternatives could have a negative impact on local manufacturing. This study examined the effects of rail abandonment in Arkansas between 1980 and 2000 by comparing measures related to manufacturing in counties that did not have or had lost some rail service with those in counties that had rail service and had not lost any. The analysis revealed no meaningful differences, suggesting the lack of any adverse economic impacts due to rail abandonment. The findings provide important insights for federal, state, and local policymakers and economic development officials; and for railroad economic development, government affairs, and strategic planning management

    Changes in Prandial Glucagon Levels After a 2-Year Treatment With Vildagliptin or Glimepiride in Patients With Type 2 Diabetes Inadequately Controlled With Metformin Monotherapy

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    OBJECTIVE - To determine if the dipeptidyl peptidase-4 inhibitor vildagliptin more effectively inhibits glucagon levels than the sulfonylurea glimepiride during a meal. RESEARCH DESIGN AND METHODS - Glucagon responses to a standard meal were measured at baseline and study end point (mean 1.8 years) in a trial evaluating add-on therapy to metformin with 50 mg vildagliptin bid. compared with glimepiride up to 6 mg q.d. in type 2 diabetes (baseline MC 7.3 +/- 0.6%). RESULTS - A1C and prandial glucose area under the curve (AUC)(0-2 h) were reduced similarly in both groups, whereas prandial insulin AUC(0-2 h) increased to a greater extent by glimepiride. Prandial glucagon AUC(0-2 h) (baseline 66.6 +/- 2.3 pmol . h(-1) . l(-1)) decreased by 3.4 +/- 1.6 pmol . h(-1) . l(-1) by vildagliptin (n = 137) and increased by 3.8 +/- 1.7 pmol . h(-1) . l(-1) by glimepiride (n = 121). The between-group difference was 7.3 +/- 2.1 pmol . h(-1) . l(-1) (P < 0.001). CONCLUSIONS - Vildagliptin therapy but not glimepiride improves postprandial a-cell function, which persists for at least 2 years

    Inhibition of Dipeptidyl Peptidase-4 by Vildagliptin During Glucagon-Like Peptide 1 Infusion Increases Liver Glucose Uptake in the Conscious Dog

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    OBJECTIVE—This study investigated the acute effects of treatment with vildagliptin on dipeptidyl peptidase-4 (DPP-4) activity, glucagon-like peptide 1 (GLP-1) concentration, pancreatic hormone levels, and glucose metabolism. The primary aims were to determine the effects of DPP-4 inhibition on GLP-1 clearance and on hepatic glucose uptake

    Accelerating Drug Development Using Biomarkers: A Case Study with Sitagliptin, A Novel DPP4 Inhibitor for Type 2 Diabetes

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    The leveraged use of biomarkers presents an opportunity in understanding target engagement and disease impact while accelerating drug development. For effective integration in drug development, it is essential for biomarkers to aid in the elucidation of mechanisms of action and disease progression. The recent years have witnessed significant progress in biomarker selection, validation, and qualification, while enabling surrogate and clinical endpoint qualification and application. Biomarkers play a central role in target validation for novel mechanisms. They also play a central role in the learning/confirming paradigm, particularly when utilized in concert with pharmacokinetic/pharmacodynamic modeling. Clearly, these attributes make biomarker integration attractive for scientific and regulatory applications to new drug development. In this review, applications of proximal, or target engagement, and distal, or disease-related, biomarkers are highlighted using the example of the recent development of sitagliptin for type 2 diabetes, wherein elucidation of target engagement and disease-related biomarkers significantly accelerated sitagliptin drug development. Importantly, use of biomarkers as tools facilitated design of clinical efficacy trials while streamlining dose focus and optimization, the net impact of which reduced overall cycle time to filing as compared to the industry average

    Introductory programming: a systematic literature review

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    As computing becomes a mainstream discipline embedded in the school curriculum and acts as an enabler for an increasing range of academic disciplines in higher education, the literature on introductory programming is growing. Although there have been several reviews that focus on specific aspects of introductory programming, there has been no broad overview of the literature exploring recent trends across the breadth of introductory programming. This paper is the report of an ITiCSE working group that conducted a systematic review in order to gain an overview of the introductory programming literature. Partitioning the literature into papers addressing the student, teaching, the curriculum, and assessment, we explore trends, highlight advances in knowledge over the past 15 years, and indicate possible directions for future research
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