29 research outputs found
Replacing Periods With Question Marks: A Study of the Role of Public Education in Kanawha County, West Virginia
In 1974 the proposal and adoption of new language arts textbooks, that sought to emphasize themes of multiculturalism and egalitarianism, sparked a violent year-long protest in Kanawha County, West Virginia. The opposition perceived the texts as overly sexual, anti-American, and intrusive while supporters celebrated the diversification of narratives and information.
The ability of newly adopted language arts textbooks to spark an explosive controversy reflects the impact of textbooks and, more broadly, public education on creating a sense of identity and belonging. Through objecting or supporting the textbooks and the language they contained, the citizens of Kanawha County were bitterly fighting to protect their own definitions of what it meant to be a good student, parent, teacher, community member, and American. Furthermore, through protesting and ultimately reworking the process of textbook adoption and inclusion, the citizens redefined who and what was included in their notion of a good public school education.
The research seeks to understand how a community’s perception of public education and the role it should play in a child’s life impacts the inclusion of the public in academic decision making as well as the insertion and definition of controversial matter in the classroom. In addition, the research seeks to better understand the triangulation of rights in public school between students, teachers, and parents
Estimating a Personalized Basal Insulin Dose from Short-Term Closed-Loop Data in Type 2 Diabetes
In type 2 diabetes (T2D) treatment, finding a safe and effective basal
insulin dose is a challenge. The dose-response is highly individual and to
ensure safety, people with T2D titrate by slowly increasing the daily insulin
dose to meet treatment targets. This titration can take months. To ease and
accelerate the process, we use short-term artificial pancreas (AP) treatment
tailored for initial titration and apply it as a diagnostic tool. Specifically,
we present a method to automatically estimate a personalized daily dose of
basal insulin from closed-loop data collected with an AP. Based on AP-data from
a stochastic simulation model, we employ the continuous-discrete extended
Kalman filter and a maximum likelihood approach to estimate parameters in a
simple dose-response model for 100 virtual people. With the identified model,
we compute a daily dose of basal insulin to meet treatment targets for each
individual. We test the personalized dose and evaluate the treatment outcomes
against clinical reference values. In the tested simulation setup, the proposed
method is feasible. However, more extensive tests will reveal whether it can be
deemed safe for clinical implementation.Comment: 6 pages, 4 figures, 1 table. Accepted for publication in Proceedings
of the 2022 61st IEEE Conference on Decision and Control (CDC
Food insecurity may be linked to childhood obesity in low-income Mexican-American families
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A Comparative Risk Assessment Of Burden Of Disease And Injury Attributable To 67 Risk Factors And Risk Factor Clusters In 21 Regions, 1990–2010: A Systematic Analysis For The Global Burden Of Disease Study 2010
Background Quantification of the disease burden caused by different risks informs prevention by providing an account of health loss different to that provided by a disease-by-disease analysis. No complete revision of global disease burden caused by risk factors has been done since a comparative risk assessment in 2000, and no previous analysis has assessed changes in burden attributable to risk factors over time
Leveraging Artificial Pancreas Technology for Treatment Optimization in T2D
In type 2 diabetes (T2D), injections with long-acting insulin can become necessary to normalize blood glucose and avoid long-term complications. However, finding a safe and effective insulin dose, a process known as titration, is both challenging and time demanding. In this thesis, we propose a new titration method for swift and safe identification of a personalized insulin dose with long-acting insulin through short-term use of rapid-acting insulin in an artificial pancreas (AP).We augment a published T2D model to simulate an AP driving the blood glucose into the clinical target range followed by a switch to injections with long-acting insulin. In simulation, the new titration method can reduce the titration period to a single week, compared to five weeks on standard-of-care titration. To explore how to best switch between rapid- and long-acting insulin, we use clinical trial data to assess the correlation between the insulin response to rapid- and long-acting insulin injections in the same individual. In an in silico cohort of a hundred people with T2D, we investigate how differences in bioavailability may influence the conversion from rapid-acting insulin delivered in a pump to an equivalent injection dose of long-acting insulin. The cohort simulation reveals that many individuals need more than one week of AP treatment to reach the clinical target range.As an alternative to letting an AP drive the blood glucose into the target range, we explore how to predict a safe and effective long-acting insulin dose from 24 to 48 hours of AP data. With simulated AP data, we estimate parameters in dose-response models using maximum likelihood estimation (MLE). We apply the continuous-discrete extended Kalman filter (CDEKF) to approximate the likelihood function which is maximized in MLE. To improve the model-based dose predictions, we apply model-based design of experiment (MBDoE) and determine how to best run an AP system to collect data for parameter estimation. Finally, we obtain personalized dose-response models from the experimental data and evaluate their ability to predict a safe and effective insulin dose for each simulated individual.In simulation, the proposed method is feasible. However, the efficacy and safety of the dose estimates heavily depend on the level of system excitation. The results indicate that MBDoE holds a potential to improve the performance of model-based dose-guidance solutions. Still, without clinical data, it is not possible to conclude on the clinical feasibility of a translating between pump- and pen-based treatment in T2D. In the future, commercial AP systems may enable clinical evaluation of the new titration method.<br/