Multivariate Long-Memory Processes and Nonparametric Density Estimation, with Applications to Ridge Detection

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Spatiotemporal dynamics of pial collateral blood flow following permanent middle cerebral artery occlusion in a rat model of sensory-based protection: a Doppler optical coherence tomography study.

There is a growing recognition regarding the importance of pial collateral flow in the protection from impending ischemic stroke both in preclinical and clinical studies. Collateral flow is also a major player in sensory stimulation-based protection from impending ischemic stroke. Doppler optical coherence tomography has been employed to image spatiotemporal patterns of collateral flow within the dorsal branches of the middle cerebral artery (MCA) as it provides a powerful tool for quantitative in vivo flow parameters imaging (velocity, flux, direction of flow, and radius of imaged branches). It was employed prior to and following dorsal permanent MCA occlusion (pMCAo) in rat models of treatment by protective sensory stimulation, untreated controls, or sham surgery controls. Unexpectedly, following pMCAo in the majority of subjects, some MCA branches continued to show anterograde blood flow patterns over time despite severing of the MCA. Further, in the presence of protective sensory stimulation, the anterograde velocity and flux were stronger and lasted longer than in retrograde flow branches, even within different branches of single subjects, but stimulated retrograde branches showed stronger flow parameters at 24 h. Our study suggests that the spatiotemporal patterns of collateral-based dorsal MCA flow are dynamic and provide a detailed description on the differential effects of protective sensory stimulation

Intersectionality-Informed Sex/Gender-Sensitivity in Public Health Monitoring and Reporting (PHMR): A Case Study Assessing Stratification on an “Intersectional Gender-Score”

To date, PHMR has often relied on male/female stratification, but rarely considers the complex, intersecting social positions of men and women in describing the prevalence of health and disease. Stratification on an Intersectional Gender-Score (IG-Score), which is based on a variety of social covariables, would allow comparison of the prevalence of individuals who share the same complex intersectional profile (IG-Score). The cross-sectional case study was based on the German Socio-Economic Panel 2017 (n = 23,269 age 18+). After stratification, covariable-balance within the total sample and IG-Score-subgroups was assessed by standardized mean differences. Prevalence of self-rated health, mental distress, depression and hypertension was compared in men and women. In the IG-Score-subgroup with highest proportion of males and lowest probability of falling into the ‘woman’-category, most individuals were in full-time employment. The IG-Score-subgroup with highest proportion of women and highest probability of falling into the ‘woman’-category was characterized by part-time/occasional employment, housewife/-husband, and maternity/parental leave. Gender differences in prevalence of health indicators remained within the male-dominated IG-Score-subgroup, whereas the same prevalence of depression and self-rated health was observed for men and women constituting the female-dominated IG-Score-subgroup. These results might indicate that sex/gender differences of depression and self-rated health could be interpreted against the background of gender associated processes. In summary, the proposed procedure allows comparison of prevalence of health indicators conditional on men and women sharing the same complex intersectional profile

Decision Tree Analyses to Explore the Relevance of Multiple Sex/Gender Dimensions for the Exposure to Green Spaces: Results from the KORA INGER Study

Recently, attention has been drawn to the need to integrate sex/gender more comprehensively into environmental health research. Considering theoretical approaches, we define sex/gender as a multidimensional concept based on intersectionality. However, operationalizing sex/gender through multiple covariates requires the usage of statistical methods that are suitable for handling such complex data. We therefore applied two different decision tree approaches: classification and regression trees (CART) and conditional inference trees (CIT). We explored the relevance of multiple sex/gender covariates for the exposure to green spaces, measured both subjectively and objectively. Data from 3742 participants from the Cooperative Health Research in the Region of Augsburg (KORA) study were analyzed within the INGER (Integrating gender into environmental health research) project. We observed that the participants’ financial situation and discrimination experience was relevant for their access to high quality public green spaces, while the urban/rural context was most relevant for the general greenness in the residential environment. None of the covariates operationalizing the individual sex/gender self-concept were relevant for differences in exposure to green spaces. Results were largely consistent for both CART and CIT. Most importantly we showed that decision tree analyses are useful for exploring the relevance of multiple sex/gender dimensions and their interactions for environmental exposures. Further investigations in larger urban areas with less access to public green spaces and with a study population more heterogeneous with respect to age and social disparities may add more information about the relevance of multiple sex/gender dimensions for the exposure to green spaces

On two sample inference for eigenspaces in functional data analysis with dependent errors

We consider functional data analysis for randomly perturbed repeated time series with a general dependence structure of the error process. Specifically, the question of testing for equality of subspaces spanned by a finite number of eigenfunctions is addressed. The asymptotic distribution of standardized residual processes based on projections of eigenfunctions is derived. A two-sample test based on the residual processes is proposed together with a nuisance parameter free bootstrap procedure. Simulations illustrate finite sample properties