Multivariate Functional Principal Component Analysis for Data Observed on Different (Dimensional) Domains

Existing approaches for multivariate functional principal component analysis are restricted to data on the same one-dimensional interval. The presented approach focuses on multivariate functional data on different domains that may differ in dimension, e.g. functions and images. The theoretical basis for multivariate functional principal component analysis is given in terms of a Karhunen-Lo\`eve Theorem. For the practically relevant case of a finite Karhunen-Lo\`eve representation, a relationship between univariate and multivariate functional principal component analysis is established. This offers an estimation strategy to calculate multivariate functional principal components and scores based on their univariate counterparts. For the resulting estimators, asymptotic results are derived. The approach can be extended to finite univariate expansions in general, not necessarily orthonormal bases. It is also applicable for sparse functional data or data with measurement error. A flexible R-implementation is available on CRAN. The new method is shown to be competitive to existing approaches for data observed on a common one-dimensional domain. The motivating application is a neuroimaging study, where the goal is to explore how longitudinal trajectories of a neuropsychological test score covary with FDG-PET brain scans at baseline. Supplementary material, including detailed proofs, additional simulation results and software is available online.Comment: Revised Version. R-Code for the online appendix is available in the .zip file associated with this article in subdirectory "/Software". The software associated with this article is available on CRAN (packages funData and MFPCA

High-Dimensional Repeated Measures

Recently, new tests for main and simple treatment effects, time effects, and treatment by time interactions in possibly high-dimensional multigroup repeated-measures designs with unequal covariance matrices have been proposed. Technical details for using more than one between-subject and more than one within-subject factor are presented in this article. Furthermore, application to electroencephalography (EEG) data of a neurological study with two whole-plot factors (diagnosis and sex) and two subplot factors (variable and region) is shown with the R package HRM (high-dimensional repeated measures)

Habituation Of Mealworm Pupae, Tenebio-Molitor Coleoptera-Tenebrionidae

In holometabolous insects, information acquired at the larval stage can persist through the intervening pupal stage and influence adult behavior (Thorpe and Jones 1937, Thorpe 1939, Borell du Vernay 1942, Borsellino et al. 1970, Somberg et al. 1970, Dethier and Goldrich 1971, Alloway 1972). To account for this relatively permanent storage of information, one must assume that those neural elements which hold this information endure through metamorphosis. The question remains: Can new information be acquired and can behavior be modified during the extensive neural reorganization that accompanies metamorphosis (Edwards 1969, Satija and Luthra 1969)? The present study indicates that a simple kind of behavior modification, namely habituation, can occur at the pupal stage during the transformation from larva to adult in Tenebrio molitor L

Pseudo-Ranks: How to Calculate Them Efficiently in R

Many popular nonparametric inferential methods are based on ranks. Among the most commonly used and most famous tests are for example the Wilcoxon-Mann-Whitney test for two independent samples, and the Kruskal-Wallis test for multiple independent groups. However, recently, it has become clear that the use of ranks may lead to paradoxical results in case of more than two groups. Luckily, these problems can be avoided simply by using pseudo-ranks instead of ranks. These pseudo-ranks, however, suffer from being (a) at first less intuitive and not as straightforward in their interpretation, (b) computationally much more expensive to calculate. The computational cost has been prohibitive, for example, for large-scale simulative evaluations or application of resampling-based pseudorank procedures. In this paper, we provide different algorithms to calculate pseudo-ranks efficiently in order to solve problem (b) and thus render it possible to overcome the current limitations of procedures based on pseudo-ranks

Increased Hematopoietic Extracellular RNAs and Vesicles in the Lung during Allergic Airway Responses.

Extracellular RNAs (exRNAs) can be released by numerous cell types in vitro, are often protected within vesicles, and can modify recipient cell function. To determine how the composition and cellular sources of exRNAs and the extracellular vesicles (EVs) that carry them change in vivo during tissue inflammation, we analyzed bronchoalveolar lavage fluid (BALF) from mice before and after lung allergen challenge. In the lung, extracellular microRNAs (ex-miRNAs) had a composition that was highly correlated with airway-lining epithelium. Using cell type-specific membrane tagging and single vesicle flow, we also found that 80% of detected vesicles were of epithelial origin. After the induction of allergic airway inflammation, miRNAs selectively expressed by immune cells, including miR-223 and miR-142a, increased and hematopoietic-cell-derived EVs also increased >2-fold. These data demonstrate that infiltrating immune cells release ex-miRNAs and EVs in inflamed tissues to alter the local extracellular environment

MicroRNA regulation of type 2 innate lymphoid cell homeostasis and function in allergic inflammation.

MicroRNAs (miRNAs) exert powerful effects on immunity through coordinate regulation of multiple target genes in a wide variety of cells. Type 2 innate lymphoid cells (ILC2s) are tissue sentinel mediators of allergic inflammation. We established the physiological requirements for miRNAs in ILC2 homeostasis and immune function and compared the global miRNA repertoire of resting and activated ILC2s and T helper type 2 (TH2) cells. After exposure to the natural allergen papain, mice selectively lacking the miR-17∼92 cluster in ILC2s displayed reduced lung inflammation. Moreover, miR-17∼92-deficient ILC2s exhibited defective growth and cytokine expression in response to IL-33 and thymic stromal lymphopoietin in vitro. The miR-17∼92 cluster member miR-19a promoted IL-13 and IL-5 production and inhibited expression of several targets, including SOCS1 and A20, signaling inhibitors that limit IL-13 and IL-5 production. These findings establish miRNAs as important regulators of ILC2 biology, reveal overlapping but nonidentical miRNA-regulated gene expression networks in ILC2s and TH2 cells, and reinforce the therapeutic potential of targeting miR-19 to alleviate pathogenic allergic responses

Outcomes Associated With Delirium in Older Patients in Surgical ICUs

BACKGROUND: We previously noted that older adults admitted to surgical ICUs (SICUs) are at high risk for delirium. In the current study, we describe the association between the presence of delirium and complications in older SICU patients, and describe the association between delirium occurring in the SICU and functional ability and discharge placement for older patients. METHODS: Secondary analysis of prospective, observational, cohort study. Subjects were 114 consecutive patients \u3eor= 65 years old admitted to a surgical critical care service. All subjects underwent daily delirium and sedation/agitation screening during hospitalization. Outcomes prospectively recorded included SICU complication development, discharge location, and functional ability (as measured by the Katz activities of daily living instrument). RESULTS: Nearly one third of older adults (31.6%) admitted to an SICU had a complication during ICU stay. There was a strong association between SICU delirium and complication occurrence (p = 0.001). Complication occurrence preceded delirium diagnosis for 16 of 20 subjects. Subjects with delirium in the SICU were more likely to be discharged to a place other than home (61.3% vs 20.5%, p \u3c 0.0001) and have greater functional decline (67.7% vs 43.6%, p = 0.023) than nondelirious subjects. After adjusting for covariates including severity of illness and mechanical ventilation use, delirium was found to be strongly and independently associated with greater odds of being discharged to a place other than home (odds ratio, 7.20; 95% confidence interval, 1.93 to 26.82). CONCLUSIONS: Delirium in older surgical ICU patients is associated with complications and an increased likelihood of discharge to a place other than home

Borrelia lonestari DNA in adult Amblyomma americanum ticks, Alabama.

Polymerase chain reaction analysis of 204 Amblyomma americanum and 28 A. maculatum ticks collected in August 1999 near the homes of patients with southern tick-associated rash illness and in control areas in Choctaw County, Alabama, showed Borrelia lonestari flagellin gene sequence from two adult A. americanum. The presence of B. lonestari in A. americanum ticks from Alabama suggests that this suspected pathogen may be widespread in the southeastern United States

Dynamic Energy Management

We present a unified method, based on convex optimization, for managing the power produced and consumed by a network of devices over time. We start with the simple setting of optimizing power flows in a static network, and then proceed to the case of optimizing dynamic power flows, i.e., power flows that change with time over a horizon. We leverage this to develop a real-time control strategy, model predictive control, which at each time step solves a dynamic power flow optimization problem, using forecasts of future quantities such as demands, capacities, or prices, to choose the current power flow values. Finally, we consider a useful extension of model predictive control that explicitly accounts for uncertainty in the forecasts. We mirror our framework with an object-oriented software implementation, an open-source Python library for planning and controlling power flows at any scale. We demonstrate our method with various examples. Appendices give more detail about the package, and describe some basic but very effective methods for constructing forecasts from historical data.Comment: 63 pages, 15 figures, accompanying open source librar