Neural networks and separation of Cosmic Microwave Background and astrophysical signals in sky maps

The Independent Component Analysis (ICA) algorithm is implemented as a neural network for separating signals of different origin in astrophysical sky maps. Due to its self-organizing capability, it works without prior assumptions on the signals, neither on their frequency scaling, nor on the signal maps themselves; instead, it learns directly from the input data how to separate the physical components, making use of their statistical independence. To test the capabilities of this approach, we apply the ICA algorithm on sky patches, taken from simulations and observations, at the microwave frequencies, that are going to be deeply explored in a few years on the whole sky, by the Microwave Anisotropy Probe (MAP) and by the {\sc Planck} Surveyor Satellite. The maps are at the frequencies of the Low Frequency Instrument (LFI) aboard the {\sc Planck} satellite (30, 44, 70 and 100 GHz), and contain simulated astrophysical radio sources, Cosmic Microwave Background (CMB) radiation, and Galactic diffuse emissions from thermal dust and synchrotron. We show that the ICA algorithm is able to recover each signal, with precision going from 10% for the Galactic components to percent for CMB; radio sources are almost completely recovered down to a flux limit corresponding to $0.7\sigma_{CMB}$, where $\sigma_{CMB}$ is the rms level of CMB fluctuations. The signal recovering possesses equal quality on all the scales larger then the pixel size. In addition, we show that the frequency scalings of the input signals can be partially inferred from the ICA outputs, at the percent precision for the dominant components, radio sources and CMB.Comment: 15 pages; 6 jpg and 1 ps figures. Final version to be published in MNRA

High-Fidelity Simulation Nurse Training Reduces Unplanned Interruption of Continuous Renal Replacement Therapy Sessions in Critically Ill Patients: The SimHeR Randomized Controlled Trial

BACKGROUND: Although continuous renal replacement therapy (CRRT) is common, unplanned interruptions (UI) often limit its usefulness. In many units, nurses are responsible for CRRT management. We hypothesized that a nurse training program based on high-fidelity simulation would reduce the rate of interrupted sessions. METHODS: We performed a 2-phase (training and evaluation), randomized, single-center, open study: During the training phase, intensive care unit nurses underwent a 6-hour training program and were randomized to receive (intervention) or not (control) an additional high-fidelity simulation training (6 hours). During the evaluation phase, management of CRRT sessions was randomized to either intervention or control nurses. Sessions were defined as UI if they were interrupted and the interruption was not prescribed in writing more than 3 hours before. RESULTS: Study nurses had experience with hemodialysis, but no experience with CRRT before training. Intervention nurses had higher scores than control nurses on the knowledge tests (grade, median [Q1-Q3], 14 [10.5-15] vs 11 [10-12]/20; P = .044). During a 13-month period, 106 sessions were randomized (n = 53/group) among 50 patients (mean age 70 ± 13 years, mean simplified acute physiology II score 69 [54-96]). Twenty-one sessions were not analyzed (4 were not performed and 17 patients died during sessions). Among the 42 intervention and 43 control sessions analyzed, 25 (59%) and 38 (88%) were labeled as UI (relative risk [95% CI], 0.67 [0.51-0.88]; P = .002). Intervention nurses required help significantly less frequently (0 [0-1] vs 3 [1-4] times/session; P < .0001). The 2 factors associated with UI in multilevel mixed-effects logistic regression were Sequential Organ Failure Assessment score (odds ratio [95% CI], 0.81 [0.65-99]; P = .047) and the intervention group (odds ratio, 0.19 [0.05-0.73]; P = .015). CONCLUSIONS: High-fidelity simulation nurse training reduced the rate of UI of CRRT sessions and the need for nurses to request assistance. This intervention may be particularly useful in the context of frequent nursing staff turnover

Physics–Dynamics Coupling in weather, climate and Earth system models: Challenges and recent progress

This is the final version. Available from American Meteorological Society via the DOI in this record.Numerical weather, climate, or Earth system models involve the coupling of components. At a broad level, these components can be classified as the resolved fluid dynamics, unresolved fluid dynamical aspects (i.e., those represented by physical parameterizations such as subgrid-scale mixing), and nonfluid dynamical aspects such as radiation and microphysical processes. Typically, each component is developed, at least initially, independently. Once development is mature, the components are coupled to deliver a model of the required complexity. The implementation of the coupling can have a significant impact on the model. As the error associated with each component decreases, the errors introduced by the coupling will eventually dominate. Hence, any improvement in one of the components is unlikely to improve the performance of the overall system. The challenges associated with combining the components to create a coherent model are here termed physics–dynamics coupling. The issue goes beyond the coupling between the parameterizations and the resolved fluid dynamics. This paper highlights recent progress and some of the current challenges. It focuses on three objectives: to illustrate the phenomenology of the coupling problem with references to examples in the literature, to show how the problem can be analyzed, and to create awareness of the issue across the disciplines and specializations. The topics addressed are different ways of advancing full models in time, approaches to understanding the role of the coupling and evaluation of approaches, coupling ocean and atmosphere models, thermodynamic compatibility between model components, and emerging issues such as those that arise as model resolutions increase and/or models use variable resolutions.Natural Environment Research Council (NERC)National Science FoundationDepartment of Energy Office of Biological and Environmental ResearchPacific Northwest National Laboratory (PNNL)DOE Office of Scienc

In vitro human growth hormone increases human chorionic gonadotropin and progesterone secretion by human placenta at term: evidence of a modulatory role by opioids

We examined the in vitro effect of human growth hormone (hGH) on hormone placental production and the modulation by opioids of this function. Small placental fragments from 12 term placentas were incubated at 37 degrees C in a 95% air and 5% CO2 atmosphere for 4 h with various concentrations of hGH (1-1000 ng/ml) or naloxone (3-500 ng/ml). Both hGH and naloxone increased the concentrations of human chorionic gonadotropin (hCG) and progesterone in the media. The effect of the hGH was dose-dependent and statistically significant at 10 ng/ml, while naloxone was able to increase hCG and progesterone production only at the highest doses (250-500 ng/ml). The concomitant treatment with ineffective doses of naloxone and hGH was able to enhance hCG and progesterone secretion reaching levels similar to those obtained with the highest doses of hGH alone. High naloxone concentrations significantly decreased both hCG and progesterone secretion induced by high doses of hGH. This study confirms the relevance of growth hormone in sustaining placental endocrine activities and indicates an effect of opioids in modulating these function

On Type I singularities of the local axi-symmetric solutions of the Navier-Stokes equations

Local regularity of axially symmetric solutions to the Navier-Stokes equations is studied. It is shown that under certain natural assumptions there are no singularities of Type I

Hawksbill turtle terra incognita: conservation genetics of eastern Pacific rookeries

Prior to 2008 and the discovery of several important hawksbill turtle (Eretmochelys imbricata) nesting colonies in the EP (Eastern Pacific), the species was considered virtually absent from the region. Research since that time has yielded new insights into EP hawksbills, salient among them being the use of mangrove estuaries for nesting. These recent revelations have raised interest in the genetic characterization of hawksbills in the EP, studies of which have remained lacking to date. Between 2008 and 2014, we collected tissue samples from 269 nesting hawksbills at nine rookeries across the EP and used mitochondrial DNA sequences (766 bp) to generate the first genetic characterization of rookeries in the region. Our results inform genetic diversity, population differentiation, and phylogeography of the species. Hawksbills in the EP demonstrate low genetic diversity: We identified a total of only seven haplotypes across the region, including five new and two previously identified nesting haplotypes (pooled frequencies of 58.4% and 41.6%, respectively), the former only evident in Central American rookeries. Despite low genetic diversity, we found strong stock structure between the four principal rookeries, suggesting the existence of multiple populations and warranting their recognition as distinct management units. Furthermore, haplotypes EiIP106 and EiIP108 are unique to hawksbills that nest in mangrove estuaries, a behavior found only in hawksbills along Pacific Central America. The detected genetic differentiation supports the existence of a novel mangrove estuary “reproductive ecotype” that may warrant additional conservation attention. From a phylogeographic perspective, our research indicates hawksbills colonized the EP via the Indo‐Pacific, and do not represent relict populations isolated from the Atlantic by the rising of the Panama Isthmus. Low overall genetic diversity in the EP is likely the combined result of few rookeries, extremely small reproductive populations and evolutionarily recent colonization events. Additional research with larger sample sizes and variable markers will help further genetic understanding of hawksbill turtles in the EP