66,975 research outputs found

    On the Stokes number and characterization of aerosol deposition in the respiratory airways

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    Aerosol deposition in the respiratory airways has traditionally been examined in terms of the Stokes number based on the reference flow timescale. This choice leads to large scatter in deposition efficiency when plotted against the reference Stokes number because the velocity and length scales experienced by advected particles deviate considerably from the reference values. A time-average of the particle local Stokes number should be adopted instead. Our results demonstrate that this average, or effective, Stokes number can deviate significantly from the reference value, in particular in the intermediate Stokes number range where variation across subjects is largest

    Mapping Functions in Health-Related Quality of Life: Mapping From Two Cancer-Specific Health-Related Quality-of-Life Instruments to EQ-5D-3L.

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    BACKGROUND: Clinical trials in cancer frequently include cancer-specific measures of health but not preference-based measures such as the EQ-5D that are suitable for economic evaluation. Mapping functions have been developed to predict EQ-5D values from these measures, but there is considerable uncertainty about the most appropriate model to use, and many existing models are poor at predicting EQ-5D values. This study aims to investigate a range of potential models to develop mapping functions from 2 widely used cancer-specific measures (FACT-G and EORTC-QLQ-C30) and to identify the best model. METHODS: Mapping models are fitted to predict EQ-5D-3L values using ordinary least squares (OLS), tobit, 2-part models, splining, and to EQ-5D item-level responses using response mapping from the FACT-G and QLQ-C30. A variety of model specifications are estimated. Model performance and predictive ability are compared. Analysis is based on 530 patients with various cancers for the FACT-G and 771 patients with multiple myeloma, breast cancer, and lung cancer for the QLQ-C30. RESULTS: For FACT-G, OLS models most accurately predict mean EQ-5D values with the best predicting model using FACT-G items with similar results using tobit. Response mapping has low predictive ability. In contrast, for the QLQ-C30, response mapping has the most accurate predictions using QLQ-C30 dimensions. The QLQ-C30 has better predicted EQ-5D values across the range of possible values; however, few respondents in the FACT-G data set have low EQ-5D values, which reduces the accuracy at the severe end. CONCLUSIONS: OLS and tobit mapping functions perform well for both instruments. Response mapping gives the best model predictions for QLQ-C30. The generalizability of the FACT-G mapping function is limited to populations in moderate to good health

    Hardness of approximation for quantum problems

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    The polynomial hierarchy plays a central role in classical complexity theory. Here, we define a quantum generalization of the polynomial hierarchy, and initiate its study. We show that not only are there natural complete problems for the second level of this quantum hierarchy, but that these problems are in fact hard to approximate. Using these techniques, we also obtain hardness of approximation for the class QCMA. Our approach is based on the use of dispersers, and is inspired by the classical results of Umans regarding hardness of approximation for the second level of the classical polynomial hierarchy [Umans, FOCS 1999]. The problems for which we prove hardness of approximation for include, among others, a quantum version of the Succinct Set Cover problem, and a variant of the local Hamiltonian problem with hybrid classical-quantum ground states.Comment: 21 pages, 1 figure, extended abstract appeared in Proceedings of the 39th International Colloquium on Automata, Languages and Programming (ICALP), pages 387-398, Springer, 201

    The Take on College Summer Fellowship Program: Impacts of College Mentorship on First-Generation and Low-Income High School Students

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    Current research on the impacts of mentorship is limited to either first-generation or low-income students if either of those identities is addressed at all. This project extends this analysis to include both identities. Using the Summer Fellowship Program organized by nonprofit Take on College, this paper delves into the profound impacts mentorship and a curated workshop curriculum can have on college and career readiness on 18 junior and senior high school students from 10 different states, all of which are first-generation and low-income. This research finds that best growth results occur on topics such as writing the personal statement, as well as financial aid. Using the data found, I will also provide recommendations for future organizers on which topics can be most beneficial for first-generation and low-income students
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