649 research outputs found
An Ensemble of Bayesian Neural Networks for Exoplanetary Atmospheric Retrieval
Machine learning is now used in many areas of astrophysics, from detecting
exoplanets in Kepler transit signals to removing telescope systematics. Recent
work demonstrated the potential of using machine learning algorithms for
atmospheric retrieval by implementing a random forest to perform retrievals in
seconds that are consistent with the traditional, computationally-expensive
nested-sampling retrieval method. We expand upon their approach by presenting a
new machine learning model, \texttt{plan-net}, based on an ensemble of Bayesian
neural networks that yields more accurate inferences than the random forest for
the same data set of synthetic transmission spectra. We demonstrate that an
ensemble provides greater accuracy and more robust uncertainties than a single
model. In addition to being the first to use Bayesian neural networks for
atmospheric retrieval, we also introduce a new loss function for Bayesian
neural networks that learns correlations between the model outputs.
Importantly, we show that designing machine learning models to explicitly
incorporate domain-specific knowledge both improves performance and provides
additional insight by inferring the covariance of the retrieved atmospheric
parameters. We apply \texttt{plan-net} to the Hubble Space Telescope Wide Field
Camera 3 transmission spectrum for WASP-12b and retrieve an isothermal
temperature and water abundance consistent with the literature. We highlight
that our method is flexible and can be expanded to higher-resolution spectra
and a larger number of atmospheric parameters
Climate Change Policies and Older Adults: An Analysis of States’ Climate Adaptation Plans
Background and Objectives
As climate change drives more frequent and intense weather events, older adults face disproportionate impacts, including having the highest mortality rates from storms, wildfires, flooding, and heat waves. State governments are critical in deploying local resources to help address climate change impacts. This policy study analyzes states’ climate adaptation plans to assess the methods through which they address the impact of climate change on older adults.
Research Design and Methods
This study uses content analysis to analyze available climate change adaptation plans for all U.S. states for strategies designed to increase resilience of older adults to impacts of climate change.
Results
Nineteen states have climate adaptation plans, of which 18 describe older adults as a population group with specific health impacts and risks factors. Four categories of adaptation strategies for older adults include communications, transportation, housing, and emergency services. State plans vary in terms of the risk factors and adaptation strategies included.
Discussion and Implications
To varying degrees, states’ climate change adaptation planning address health, social and economic risks specific to older adults, as well as strategies for mitigating those risks. As global warming continues, collaborations between public and private sectors and across regions will be needed to prevent negative outcomes such as forced relocation and other social and economic disruptions as well as disparate morbidity and mortality
Extreme Heat Vulnerability among Older Adults: A Multi-level Risk Index for Portland, Oregon
Background and Objectives
Extreme heat is an environmental health equity concern disproportionately impacting low-income older adults and people of color. Exposure factors, such as living in rental housing and lack of air conditioning, and sensitivity factors, such as chronic disease and social isolation, increase mortality risk among older adults. Older persons face multiple barriers to adaptive heat mitigation, particularly for those living in historically temperate climates. This study measures two heat vulnerability indices to identify areas and individuals most vulnerable to extreme heat and discusses opportunities to mitigate vulnerability among older adults.
Research Design and Methods
We constructed two heat vulnerability indices for the Portland, Oregon metropolitan area: one using area scale proxy measures extracted from existing regional data and another at the individual scale using survey data collected following the 2021 Pacific Northwest Heat Dome event. These indices were analyzed using principal component analysis (PCA) and Geographic Information Systems (GIS).
Results
Results indicate that the spatial distribution of areas and individuals vulnerable to extreme heat are quite different. The only area found among the most vulnerable on both indices has the largest agglomeration of age- and income-restricted rental housing in the metropolitan area
[11C]flumazenil Binding Is Increased in a Dose-Dependent Manner with Tiagabine-Induced Elevations in GABA Levels
Evidence indicates that synchronization of cortical activity at gamma-band frequencies, mediated through GABA-A receptors, is important for perceptual/cognitive processes. To study GABA signaling in vivo, we recently used a novel positron emission tomography (PET) paradigm measuring the change in binding of the benzodiazepine (BDZ) site radiotracer [11C]flumazenil associated with increases in extracellular GABA induced via GABA membrane transporter (GAT1) blockade with tiagabine. GAT1 blockade resulted in significant increases in [11C]flumazenil binding potential (BPND) over baseline in the major functional domains of the cortex, consistent with preclinical studies showing that increased GABA levels enhance the affinity of GABA-A receptors for BDZ ligands. In the current study we sought to replicate our previous results and to further validate this approach by demonstrating that the magnitude of increase in [11C]flumazenil binding observed with PET is directly correlated with tiagabine dose. [11C]flumazenil distribution volume (VT) was measured in 18 healthy volunteers before and after GAT1 blockade with tiagabine. Two dose groups were studied (n = 9 per group; Group I: tiagabine 0.15 mg/kg; Group II: tiagabine 0.25 mg/kg). GAT1 blockade resulted in increases in mean (± SD) [11C]flumazenil VT in Group II in association cortices (6.8±0.8 mL g−1 vs. 7.3±0.4 mL g−1;p = 0.03), sensory cortices (6.7±0.8 mL g−1 vs. 7.3±0.5 mL g−1;p = 0.02) and limbic regions (5.2±0.6 mL g−1 vs. 5.7±0.3 mL g−1;p = 0.03). No change was observed at the low dose (Group I). Increased orbital frontal cortex binding of [11C]flumazenil in Group II correlated with the ability to entrain cortical networks (r = 0.67, p = 0.05) measured via EEG during a cognitive control task. These data provide a replication of our previous study demonstrating the ability to measure in vivo, with PET, acute shifts in extracellular GABA
Winter Movements of Louisiana Pine Snakes (Pituophis ruthveni) in Texas and Louisiana
Despite concerns that the Louisiana Pine Snake (Pituophis ruthveni) has been extirpated from large portions of its historic range, only a limited number of studies on their movement patterns have been published. Winter movement patterns are of particular interest since it has been hypothesized that impacts of management practices would be reduced during the winter. Using radiotelemetry, we determined winter movement patterns of Louisiana Pine Snakes (11 males, 8 females) in 5 study areas (2 in Louisiana and 3 in Texas). Movements during winter (November–February) were greatly curtailed compared to the remainder of the year; however, snakes occasionally undertook substantial movements. Relocations were typically within the snake’s previous active-season home range, and movements were more frequent in the early portion of winter. All hibernation sites were within Baird’s Pocket Gopher (Geomys breviceps) burrow systems at depths ranging from 13–25 cm. Louisiana Pine Snakes did not use communal hibernacula, nor did individual snakes return to previously used sites in successive years
Prey handling and diet of Louisiana pine snakes (Pituophis ruthveni) and black pine snakes (P. melanoleucus lodingi), with comparisons to other selected colubrid snakes
Diet and prey handling behavior were determined for Louisiana pine snakes (Pituophis ruthveni) and black pine snakes (P. melanoleucus lodingi). Louisiana pine snakes prey heavily on Baird\u27s pocket gophers (Geomys breviceps), with which they are sympatric, and exhibit specialized behaviors that facilitate handling this prey species within the confines of burrow systems. Black pine snakes, which are not sympatric with pocket gophers, did not exhibit these specialized behaviors. For comparative purposes, prey handling of P. sayi sayi and Elaphe obsoleta lindheimeri was also examined
Accurate Machine Learning Atmospheric Retrieval via a Neural Network Surrogate Model for Radiative Transfer
Atmospheric retrieval determines the properties of an atmosphere based on its
measured spectrum. The low signal-to-noise ratio of exoplanet observations
require a Bayesian approach to determine posterior probability distributions of
each model parameter, given observed spectra. This inference is computationally
expensive, as it requires many executions of a costly radiative transfer (RT)
simulation for each set of sampled model parameters. Machine learning (ML) has
recently been shown to provide a significant reduction in runtime for
retrievals, mainly by training inverse ML models that predict parameter
distributions, given observed spectra, albeit with reduced posterior accuracy.
Here we present a novel approach to retrieval by training a forward ML
surrogate model that predicts spectra given model parameters, providing a fast
approximate RT simulation that can be used in a conventional Bayesian retrieval
framework without significant loss of accuracy. We demonstrate our method on
the emission spectrum of HD 189733 b and find good agreement with a traditional
retrieval from the Bayesian Atmospheric Radiative Transfer (BART) code
(Bhattacharyya coefficients of 0.9843--0.9972, with a mean of 0.9925, between
1D marginalized posteriors). This accuracy comes while still offering
significant speed enhancements over traditional RT, albeit not as much as ML
methods with lower posterior accuracy. Our method is ~9x faster per parallel
chain than BART when run on an AMD EPYC 7402P central processing unit (CPU).
Neural-network computation using an NVIDIA Titan Xp graphics processing unit is
90--180x faster per chain than BART on that CPU.Comment: 16 pages, 4 figures, submitted to PSJ 3/4/2020, revised 1/22/2021.
Text restructured and updated for clarity, model updated and expanded to work
for range of hot Jupiters, results/plots updated, two new appendices to
further justify model selection and methodolog
Structures and processes of care in ambulatory oncology settings and nurse-reported exposure to chemotherapy
PURPOSE:
Oncology nurses in ambulatory settings are at increased risk for unintentional chemotherapy exposure due to the large volumes of agents delivered and the absence of regulatory enforcement. Given the limited data regarding the correlates of exposure, the authors sought to identify the relationship between the organisational structures and processes of care in ambulatory oncology settings associated with increased risk of unintentional chemotherapy.
METHODS:
Between April 2010 and June 2010, a state-wide sample of oncology nurses were surveyed who reported their employment outside of hospital inpatient units (n=1339). The survey examined the likelihood of self-reported exposure to chemotherapy as a function of perceived quality of the practice environment, nursing workload, and seven ambulatory chemotherapy administration safety standards.
RESULTS:
The response rate was 30.4%, with minimal demographic differences observed between respondents and non-respondents. The overall rate of exposure to the skin or eyes in the past year was 16.9%. In multivariable logistic regression models that controlled for demographic characteristics and clustering of nurses in practices, the likelihood of exposure decreased when nurses reported adequate staffing and resources (OR 0.35, 95% CI 0.17 to 0.73; p=0.001), and when nurses reported that chemotherapy doses were verified by two nurses frequently or very frequently (OR 0.17, 95% CI 0.05 to 0.59; p=0.001).
CONCLUSIONS:
Oncology nurses in the ambulatory setting report substantial unintentional skin and eye exposure to chemotherapy. Ensuring adequate staffing and resources and adherence to recognised practice standards may protect oncology nurses from harm.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/94114/1/Structures and processes of care in ambulatory oncology settings and nurse-reported exposure to chemotherapy.pd
ITGB5 and AGFG1 variants are associated with severity of airway responsiveness
Background: Airway hyperresponsiveness (AHR), a primary characteristic of asthma, involves increased airway smooth muscle contractility in response to certain exposures. We sought to determine whether common genetic variants were associated with AHR severity. Methods: A genome-wide association study (GWAS) of AHR, quantified as the natural log of the dosage of methacholine causing a 20% drop in FEV1, was performed with 994 non-Hispanic white asthmatic subjects from three drug clinical trials: CAMP, CARE, and ACRN. Genotyping was performed on Affymetrix 6.0 arrays, and imputed data based on HapMap Phase 2, was used to measure the association of SNPs with AHR using a linear regression model. Replication of primary findings was attempted in 650 white subjects from DAG, and 3,354 white subjects from LHS. Evidence that the top SNPs were eQTL of their respective genes was sought using expression data available for 419 white CAMP subjects. Results: The top primary GWAS associations were in rs848788 (P-value 7.2E-07) and rs6731443 (P-value 2.5E-06), located within the ITGB5 and AGFG1 genes, respectively. The AGFG1 result replicated at a nominally significant level in one independent population (LHS P-value 0.012), and the SNP had a nominally significant unadjusted P-value (0.0067) for being an eQTL of AGFG1. Conclusions: Based on current knowledge of ITGB5 and AGFG1, our results suggest that variants within these genes may be involved in modulating AHR. Future functional studies are required to confirm that our associations represent true biologically significant findings
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