This paper presents a system of hybrid models that combine both mechanistic and data-driven approaches to predict physical powder blend properties from their raw component properties. Mechanistic, probabilistic models were developed to predict the particle size and shape, represented by aspect ratio, distributions of pharmaceutical blends using those of the raw components. Additionally, the accuracy of existing mixture rules for predicting the blend's true density and bulk density was assessed.
View Article and Find Full Text PDFObjective: Across two experiments, we examined three cognitive biases (order effects, context effects, confirmatory bias) in licensed psychologists' diagnostic reasoning.
Hypotheses: Our main prediction was that psychologist-participants would seek confirming versus disconfirming information after forming an initial diagnostic hypothesis, even given multiple opportunities to seek new information in the same case. We also expected that individual differences would affect diagnostic reasoning, such that psychologists with lower (vs.
In this study, a compartmental disintegration and dissolution model is proposed for the prediction and evaluation of the dissolution performance of directly compressed tablets. This dissolution model uses three compartments (Bound, Disintegrated, and Dissolved) to describe the state of each particle of active pharmaceutical ingredient. The disintegration of the tablet is captured by three fitting parameters.
View Article and Find Full Text PDFBMJ Mil Health
January 2025
Prone positioning is an intervention used for patients with acute respiratory distress syndrome (ARDS) whose hypoxia is worsening despite conventional treatment. Previously used infrequently, it became an important treatment escalation strategy for hypoxia during the COVID-19 pandemic. Current evidence for prone positioning suggests increased survivability in intubated patients with moderate to severe ARDS who are prone for >12 hours a day.
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