Context matters: Construct framing in measures of physical activity engagement among African American women

Assessment of psychosocial factors influencing health behavior typically privileges conceptual consistency (framing constructs similarly across contexts) over conceptual specificity (context-specific framing). Modest statistical relationships between these factors and health behaviors, and persistent racial disparities in health outcomes raise questions about whether conceptually consistent framing fully captures relevant predictors. Ethnographic studies suggest not - that perceptions influencing health behaviors are multifaceted and contextual. To test this, we added items querying contextualized predictors of intention to engage in leisure-time physical activity (LTPA) to a Theory of Planned Behavior (TPB)-based survey and examined the psychometrics of the adapted subscales. We measured internal consistency (Cronbach’s alpha) and construct validity (exploratory factor analysis using polychoric correlations for ordinal data). Participants were a convenience sample of 200 African American women in a Midwestern, suburban University-affiliated family medicine practice. Reliability of the adapted subscales was notably lower than the original subscales. A two-factor model fit best for the attitudes subscale, but explained slightly less than 50% of the variance. The new items loaded strongly on one factor. A three-factor model best fit the norms subscale and accounted for around 57% of the variance. Two of the three new items loaded strongly on one factor. Factor analysis for the perceived control subscale was not possible due to low number of items; however, two of the three new items were highly correlated (.73). Including context-specific factors may improve assessment of intention to engage in LTPA. Further study of this question with a larger, representative sample is warranted

Nonrandom Territory Occupancy by Nesting Gyrfalcons (\u3ci\u3eFalco rusticolus\u3c/i\u3e)

We know little regarding how specific aspects of habitat influence spatial variation in site occupancy by Arctic wildlife, yet this information is fundamental to effective conservation. To address this information gap, we assessed occupancy of 84 Gyrfalcon (Falco rusticolus Linnaeus, 1758) breeding territories observed annually between 2004 and 2013 in western Alaska. In line with the theory of population regulation by site dependence, we asked whether Gyrfalcons exhibited a nonrandom pattern of site selection and if heterogeneous landscape attributes correlated with observed occupancy patterns. We characterized high- and low-occupancy breeding territories as those occupied more or less often than expected by chance, and we evaluated land cover at 1 and 15 km circles centered around nesting territories to identify habitat variables associated with observed occupancy patterns. We tested 15 competing models to rank hypotheses reflecting prey and habitat variables important to nesting Gyrfalcons. We confirmed a nonrandom pattern of site selection but found only weak evidence that the distribution of prey habitat was responsible for this pattern. We reason that preferential habitat use by nesting Gyrfalcons may be determined by spatial scales other than those we measured or may be driven by landscape-level attributes at time periods other than during the brood rearing period

Progress on lead-free metal halide perovskites for photovoltaic applications: a review

ABSTRACT: Metal halide perovskites have revolutionized the field of solution-processable photovoltaics. Within just a few years, the power conversion efficiencies of perovskite-based solar cells have been improved significantly to over 20%, which makes them now already comparably efficient to silicon-based photovoltaics. This breakthrough in solution-based photovoltaics, however, has the drawback that these high efficiencies can only be obtained with lead-based perovskites and this will arguably be a substantial hurdle for various applications of perovskite-based photovoltaics and their acceptance in society, even though the amounts of lead in the solar cells are low. This fact opened up a new research field on lead-free metal halide perovskites, which is currently remarkably vivid. We took this as incentive to review this emerging research field and discuss possible alternative elements to replace lead in metal halide perovskites and the properties of the corresponding perovskite materials based on recent theoretical and experimental studies. Up to now, tin-based perovskites turned out to be most promising in terms of power conversion efficiency; however, also the toxicity of these tin-based perovskites is argued. In the focus of the research community are other elements as well including germanium, copper, antimony, or bismuth, and the corresponding perovskite compounds are already showing promising properties. GRAPHICAL ABSTRACT: [Image: see text

Grain Diversity Effects on Banker Plant Growth and Parasitism by Aphidius colemani

Green peach aphid (Myzus persicae Sulzer) (Hemiptera: Aphididae) is a serious greenhouse pest with a short generation time, parthenogenetic reproduction and a broad host range. Banker plant systems are becoming a more common form of biological control for this pest. This system consists of grain “banker plants” infested with R. padi, an alternative hosts for the parasitoid Aphidius colemani. Thus A. colemani can reproduce on the banker plant when M. persicae populations are low. This system can increase pest suppression; however, like other biological control tools, efficacy is inconsistent. One reason is because several different grain species have been used. Our studies determined if there were benefits to planting interspecific mixture banker plants, similar to when open agricultural systems use mixed cropping. Our study found that although banker plants grow larger when planted as mixtures this added plant growth does not increase in the number of aphids, or mummies an individual banker plant can sustain. Rye banker plants grew larger, and sustained more mummies than the other species we tested, but barley banker plants resulted in a similar number of aphids in a more condensed area. Ultimately, we did not see any differences in pest suppression between monoculture banker plants, mixture banker plants, or our augmentative release treatment. However, using banker plants resulted in more female parasitoids than the augmentative release, a benefit to using banker plant systems

Implementation of Engine Loss Analysis Methods in the Numerical Propulsion System Simulation

Proceedings of ASME Turbo Expo 2005: Land Sea & Air, June 6-9, 2005, Reno-Tahoe, NevadaThis paper describes the implementation and application of a new set of thermodynamic loss analysis tools in the Numerical Propulsion System Simulation. This analysis tool set is intended to enable fast, accurate estimation of losses in an engine cycle model with minimal effort on the part of the user. The basic thermodynamic concepts and analysis methods are first described. Next, the implementation of the necessary thermodynamic calculation functions is described. These functions are intended to be used in conjunction with a generalpurpose loss analysis element to facilitate estimation of all losses in an engine cycle model. The loss analysis element is described in detail and is subsequently used to analyze a mixed flow turbofan engine. Typical performance and loss results are presented. The resultant detailed loss information is not normally available when using standard cycle analysis methods. The information gained from this analysis is useful in that it yields insight into the underlying losses that contribute to the overall engine performance

Gut metabolites predict Clostridioides difficile recurrence

This repository contains: 1. Data used for analyses from: A) 16S rRNA gene amplicon analysis after paired-end Fastq files were truncated, filtered, denoised, and merged ["1-ASV_Counts.xlsx"] B) Untargeted metabolomics as provided by Metabolon ["2-UntargetedMetabolomics.xlsx"] C) Precision SCFA analysis ["3-PrecisionSCFA.xlsx"] D) Clincal demographic data of the study cohort ["Clinical Demographics.csv"] 2. Detailed results of univariate analyses in sub-folder "Univariate analysis results" for clinical data, untargeted metabolomics data, SCFAs, and ASVs 3. Detailed results of predictive analysis in subfolder "Predictive Analyses results", including per-fold performance results ("9-PredictiveResults.xlsx") and analysis of predictive features for ASVs ("10-ASVsPredictiveAnalysis.xlsx"), untargeted metabolites ("11-MetabsPredictiveAnalysis.xlsx"), targeted SCFAs ("12-SCFAPredictive Analysis.xlsx"), clinical data ("13-DemoPredictiveAnalysis.xlsx") and all data ("14-AllDataPredictiveAnalysis.xlsx") 4. Data for generating all figures and analyses in the publication ("GenFigure&AnalysesData"

Gut metabolites predict Clostridioides difficile recurrence

Abstract Background Clostridioides difficile infection (CDI) is the most common hospital acquired infection in the USA, with recurrence rates > 15%. Although primary CDI has been extensively linked to gut microbial dysbiosis, less is known about the factors that promote or mitigate recurrence. Moreover, previous studies have not shown that microbial abundances in the gut measured by 16S rRNA amplicon sequencing alone can accurately predict CDI recurrence. Results We conducted a prospective, longitudinal study of 53 non-immunocompromised participants with primary CDI. Stool sample collection began pre-CDI antibiotic treatment at the time of diagnosis, and continued up to 8 weeks post-antibiotic treatment, with weekly or twice weekly collections. Samples were analyzed using (1) 16S rRNA amplicon sequencing, (2) liquid chromatography/mass-spectrometry metabolomics measuring 1387 annotated metabolites, and (3) short-chain fatty acid profiling. The amplicon sequencing data showed significantly delayed recovery of microbial diversity in recurrent participants, and depletion of key anaerobic taxa at multiple time-points, including Clostridium cluster XIVa and IV taxa. The metabolomic data also showed delayed recovery in recurrent participants, and moreover mapped to pathways suggesting distinct functional abnormalities in the microbiome or host, such as decreased microbial deconjugation activity, lowered levels of endocannabinoids, and elevated markers of host cell damage. Further, using predictive statistical/machine learning models, we demonstrated that the metabolomic data, but not the other data sources, can accurately predict future recurrence at 1 week (AUC 0.77 [0.71, 0.86; 95% interval]) and 2 weeks (AUC 0.77 [0.69, 0.85; 95% interval]) post-treatment for primary CDI. Conclusions The prospective, longitudinal, and multi-omic nature of our CDI recurrence study allowed us to uncover previously unrecognized dynamics in the microbiome and host presaging recurrence, and, in particular, to elucidate changes in the understudied gut metabolome. Moreover, we demonstrated that a small set of metabolites can accurately predict future recurrence. Our findings have implications for development of diagnostic tests and treatments that could ultimately short-circuit the cycle of CDI recurrence, by providing candidate metabolic biomarkers for diagnostics development, as well as offering insights into the complex microbial and metabolic alterations that are protective or permissive for recurrence. Video Abstrac