29 research outputs found

    Space station accommodations for lunar base elements: A study

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    The results of a study conducted at NASA-LaRC to assess the impact on the space station of accommodating a Manned Lunar Base are documented. Included in the study are assembly activities for all infrastructure components, resupply and operations support for lunar base elements, crew activity requirements, the effect of lunar activities on Cape Kennedy operations, and the effect on space station science missions. Technology needs to prepare for such missions are also defined. Results of the study indicate that the space station can support the manned lunar base missions with the addition of a Fuel Depot Facility and a heavy lift launch vehicle to support the large launch requirements

    Morphometric evaluation of the delayed cerebral arteries response to acetazolamide test in patients with chronic carotid artery stenosis using computed tomography angiography

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    Background: The evidence accumulates that the response to acetazolamide test is delayed on the ipsilateral side to stenosis. However, the effect of acetazolamide beyond 30 min after acetazolamide administration remains unknown. The aim of this study was to assess the diameters of anterior cerebral arteries (ACAs), middle cerebral arteries (MCAs) and posterior cerebral arteries (PCAs) before and 60 min after the acetazolamide test. Materials and methods: Seventeen patients with carotid artery stenosis ≥ 90% on the ipsilateral side and ≤ 50% on the contralateral side were enrolled into the study. Diagnosis was based on ultrasonography examination and was confirmed using digital subtractive angiography. In all patients, two computed tomography angiography examinations were carried out; the first was performed before the acetazolamide administration, while the second one was carried out 60 min after injections. Results: In response to the acetazolamide test: PCA diameter diminished in both ipsi- and contra-lateral side to stenosis (from 1.31 to 1.24 mm and from 1.23 to 1.15 mm, respectively), ACA and MCA decreased in the contralateral side to the stenosis (from 1.33 to 1.26 mm and from 2.75 to 2.66 mm, respectively), ACA and MCA increased in the ipsilateral side to the stenosis (from 1.29 to 1.46 mm and from 2.77 to 2.96 mm, respectively). All changes were statistically significant. Conclusions: There were significant differences in reactivity to acetazolamide challenge between the internal carotid artery (ICA) and vertebrobasilar circulation in patients suffering from chronic carotid artery stenosis. Within the ICA territory, ACA and MCA responses vary in the affected and not affected side.

    Many analysts, one data set: making transparent how variations in analytic choices affect results

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    Twenty-nine teams involving 61 analysts used the same data set to address the same research question: whether soccer referees are more likely to give red cards to dark-skin-toned players than to light-skin-toned players. Analytic approaches varied widely across the teams, and the estimated effect sizes ranged from 0.89 to 2.93 (Mdn = 1.31) in odds-ratio units. Twenty teams (69%) found a statistically significant positive effect, and 9 teams (31%) did not observe a significant relationship. Overall, the 29 different analyses used 21 unique combinations of covariates. Neither analysts’ prior beliefs about the effect of interest nor their level of expertise readily explained the variation in the outcomes of the analyses. Peer ratings of the quality of the analyses also did not account for the variability. These findings suggest that significant variation in the results of analyses of complex data may be difficult to avoid, even by experts with honest intentions. Crowdsourcing data analysis, a strategy in which numerous research teams are recruited to simultaneously investigate the same research question, makes transparent how defensible, yet subjective, analytic choices influence research results

    A many-analysts approach to the relation between religiosity and well-being

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    The relation between religiosity and well-being is one of the most researched topics in the psychology of religion, yet the directionality and robustness of the effect remains debated. Here, we adopted a many-analysts approach to assess the robustness of this relation based on a new cross-cultural dataset (N=10,535 participants from 24 countries). We recruited 120 analysis teams to investigate (1) whether religious people self-report higher well-being, and (2) whether the relation between religiosity and self-reported well-being depends on perceived cultural norms of religion (i.e., whether it is considered normal and desirable to be religious in a given country). In a two-stage procedure, the teams first created an analysis plan and then executed their planned analysis on the data. For the first research question, all but 3 teams reported positive effect sizes with credible/confidence intervals excluding zero (median reported β=0.120). For the second research question, this was the case for 65% of the teams (median reported β=0.039). While most teams applied (multilevel) linear regression models, there was considerable variability in the choice of items used to construct the independent variables, the dependent variable, and the included covariates

    A Many-analysts Approach to the Relation Between Religiosity and Well-being

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    The relation between religiosity and well-being is one of the most researched topics in the psychology of religion, yet the directionality and robustness of the effect remains debated. Here, we adopted a many-analysts approach to assess the robustness of this relation based on a new cross-cultural dataset (N = 10, 535 participants from 24 countries). We recruited 120 analysis teams to investigate (1) whether religious people self-report higher well-being, and (2) whether the relation between religiosity and self-reported well-being depends on perceived cultural norms of religion (i.e., whether it is considered normal and desirable to be religious in a given country). In a two-stage procedure, the teams first created an analysis plan and then executed their planned analysis on the data. For the first research question, all but 3 teams reported positive effect sizes with credible/confidence intervals excluding zero (median reported β = 0.120). For the second research question, this was the case for 65% of the teams (median reported β = 0.039). While most teams applied (multilevel) linear regression models, there was considerable variability in the choice of items used to construct the independent variables, the dependent variable, and the included covariates

    Same data, different conclusions: Radical dispersion in empirical results when independent analysts operationalize and test the same hypothesis

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    In this crowdsourced initiative, independent analysts used the same dataset to test two hypotheses regarding the effects of scientists’ gender and professional status on verbosity during group meetings. Not only the analytic approach but also the operationalizations of key variables were left unconstrained and up to individual analysts. For instance, analysts could choose to operationalize status as job title, institutional ranking, citation counts, or some combination. To maximize transparency regarding the process by which analytic choices are made, the analysts used a platform we developed called DataExplained to justify both preferred and rejected analytic paths in real time. Analyses lacking sufficient detail, reproducible code, or with statistical errors were excluded, resulting in 29 analyses in the final sample. Researchers reported radically different analyses and dispersed empirical outcomes, in a number of cases obtaining significant effects in opposite directions for the same research question. A Boba multiverse analysis demonstrates that decisions about how to operationalize variables explain variability in outcomes above and beyond statistical choices (e.g., covariates). Subjective researcher decisions play a critical role in driving the reported empirical results, underscoring the need for open data, systematic robustness checks, and transparency regarding both analytic paths taken and not taken. Implications for organizations and leaders, whose decision making relies in part on scientific findings, consulting reports, and internal analyses by data scientists, are discussed

    A many-analysts approach to the relation between religiosity and well-being

    Get PDF
    The relation between religiosity and well-being is one of the most researched topics in the psychology of religion, yet the directionality and robustness of the effect remains debated. Here, we adopted a many-analysts approach to assess the robustness of this relation based on a new cross-cultural dataset (N=10,535 participants from 24 countries). We recruited 120 analysis teams to investigate (1) whether religious people self-report higher well-being, and (2) whether the relation between religiosity and self-reported well-being depends on perceived cultural norms of religion (i.e., whether it is considered normal and desirable to be religious in a given country). In a two-stage procedure, the teams first created an analysis plan and then executed their planned analysis on the data. For the first research question, all but 3 teams reported positive effect sizes with credible/confidence intervals excluding zero (median reported β=0.120). For the second research question, this was the case for 65% of the teams (median reported β=0.039). While most teams applied (multilevel) linear regression models, there was considerable variability in the choice of items used to construct the independent variables, the dependent variable, and the included covariates

    Determining crystal structures through crowdsourcing and coursework

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    We show here that computer game players can build high-quality crystal structures. Introduction of a new feature into the computer game Foldit allows players to build and real-space refine structures into electron density maps. To assess the usefulness of this feature, we held a crystallographic model-building competition between trained crystallographers, undergraduate students, Foldit players and automatic model-building algorithms. After removal of disordered residues, a team of Foldit players achieved the most accurate structure. Analysing the target protein of the competition, YPL067C, uncovered a new family of histidine triad proteins apparently involved in the prevention of amyloid toxicity. From this study, we conclude that crystallographers can utilize crowdsourcing to interpret electron density information and to produce structure solutions of the highest quality

    Case study, effective waste minimization using ion exchange technology

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