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Proposal for sustaining STARS (Sisters Transportation and Ride Share): transition to an independent non-profit, providing non-emergency transportation services in Sisters, Oregon
Get PDFIn 2025, STARS (Sisters Transportation and Ride Share) organization in Sisters, Oregon aims to transition to an independent 501(c)(3) organization. For organizational sustainability, it needs to establish an optimal organizational staff, structure, and governance model, while also exploring business partnerships and securing reliable funding avenues. Sustaining STARS will ensure that the residents of Sisters, Oregon continue to have access to non-emergency medical transportation. Our objective is to offer recommendations to facilitate this successful transition
Absenteeism in the public schools
Get PDFIn consideration of the affections causing absences it has been necessary to depend upon morbidity statistics compiled largely by the United States Bureau pf the Public health and a few summaries from single institutions. The conclusions drawn from the tables and figures included in this paper might give one a concrete conception - allowance must be made since morbidity statistics are difficult to gather and since opinion varies greatly in minor diagnoses and as to extent and severity of illnesses recorded. Several classifications of the causes of absenteeism have been made
Does changing items' contexts impact a scale's psychometric properties? A comparison using the perma-profiler and the workplace wellbeing survey
Get PDFScales are often adapted for the context in which they are used, which may involve simply adjusting items to orient the respondent to the study’s focal context. However, if a scale’s items are adapted to be context-specific (e.g., moving from general to workplace), will its psychometric properties change? This study aimed to investigate this question by evaluating measurement and structural equivalence of the PERMA-Profiler (PP) and its workplace adaptation, the Workplace Wellbeing Survey (WWS)
Mechanistic deep learning for perturbation biology: application to precision oncology
Get PDFThe work presented in this dissertation focuses on the development of robust deep learning models to predict in-vitro cancer drug responses, with utility in precision oncology research tasks such as drug repurposing and prioritization of disease-specific drug combinations. This work addresses two critical shortcomings in the current approaches to predicting cancer drug responses with deep learning: 1) data quality issues inherent in high-throughput drug screening datasets by developing algorithms for detection of atypical or low-quality data and 2) improved prediction and utility of perturbation biology models by developing algorithms that operate on mechanistic prior knowledge
Dietary intake and plasma acylcarnitine among LCHADD/TFPD participants
Get PDFThis study describes the usual intake including supplements of participants aged 2-36 years old with LCHADD/TFPD. The effect of medium- and long-chain fat consumption on fasting plasma acylcarnitine concentrations were also assessed