868 research outputs found
Quantification of Linear and Nonlinear Cardiorespiratory Interactions under Autonomic Nervous System Blockade
This paper proposes a methodology to extract both linear and nonlinear respiratory influences from the heart rate variability (HRV), by decomposing the HRV into a respiratory and a residual component. This methodology is based on least-squares support vector machines (LS-SVM) formulated for nonlinear function estimation. From this decomposition, a better estimation of the respiratory sinus arrhythmia (RSA) and the sympathovagal balance (SB) can be achieved. These estimates are first analyzed during autonomic blockade and an orthostatic maneuver, and then compared against the classical HRV and a model that considers only linear interactions. Results are evaluated using surrogate data analysis and they indicate that the classical HRV and the linear model underestimate the cardiorespiratory interactions. Moreover, the linear and nonlinear interactions appear to be mediated by different control mechanisms. These findings will allow to better assess the ANS and to improve the understanding of the interactions within the cardiorespiratory system
Detecting and quantifying methane emissions from oil and gas production: algorithm development with ground-truth calibration based on Sentinel-2 satellite imagery
Sentinel-2 satellite imagery has been shown by studies to be
capable of detecting and quantifying methane emissions from oil and gas
production. However, current methods lack performance calibration with
ground-truth testing. This study developed a multi-band–multi-pass–multi-comparison-date methane retrieval algorithm that enhances Sentinel-2 sensitivity to methane plumes. The method was calibrated
using data from a large-scale controlled-release test in Ehrenberg, Arizona,
in fall 2021, with three algorithm parameters tuned based on the true
emission rates. Tuned parameters are the pixel-level concentration upper-bound threshold during extreme value removal, the number of comparison
dates, and the pixel-level methane concentration percentage threshold when
determining the spatial extent of a plume. We found that a low value of the
upper-bound threshold during extreme value removal can result in false
negatives. A high number of comparison dates helps enhance the algorithm
sensitivity to the plumes in the target date, but values in excess of
12 d are neither necessary nor computationally efficient. A high percentage
threshold when determining the spatial extent of a plume helps enhance the
quantification accuracy, but it may harm the yes/no detection accuracy. We
found that there is a trade-off between quantification accuracy and
detection accuracy. In a scenario with the highest quantification accuracy,
we achieved the lowest quantification error and had zero false-positive
detections; however, the algorithm missed three true plumes, which reduced the
yes/no detection accuracy. In contrast, all of the true plumes were
detected in the highest detection accuracy scenario, but the emission rate
quantification had higher errors. We illustrated a two-step method that
updates the emission rate estimates in an interim step, which improves
quantification accuracy while keeping high yes/no detection accuracy. We
also validated the algorithm's ability to detect true positives and true
negatives in two application studies.</p
Demersal fish assemblages on seamounts and other rugged features in the northeastern Caribbean
© The Author(s), 2017. This is the author's version of the work and is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Deep Sea Research Part I: Oceanographic Research Papers 123 (2017): 90–104, doi:10.1016/j.dsr.2017.03.009.Recent investigations of demersal fish communities in deepwater (>50 m) habitats have considerably increased our knowledge of the factors that influence the assemblage structure of fishes across mesophotic to deep-sea depths. While different habitat types influence deepwater fish distribution, whether different types of rugged seafloor features provide functionally equivalent habitat for fishes is poorly understood. In the northeastern Caribbean, different types of rugged features (e.g., seamounts, banks, canyons) punctuate insular margins, and thus create a remarkable setting in which to compare demersal fish communities across various features. Concurrently, several water masses are vertically layered in the water column, creating strong stratification layers corresponding to specific abiotic conditions. In this study, we examined differences among fish assemblages across different features (e.g., seamount, canyon, bank/ridge) and water masses at depths ranging from 98 to 4060 m in the northeastern Caribbean. We conducted 26 remotely operated vehicle dives across 18 sites, identifying 156 species of which 42% of had not been previously recorded from particular depths or localities in the region. While rarefaction curves indicated fewer species at seamounts than at other features in the NE Caribbean, assemblage structure was similar among the different types of features. Thus, similar to seamount studies in other regions, seamounts in the Anegada Passage do not harbor distinct communities from other types of rugged features. Species assemblages, however, differed among depths, with zonation generally corresponding to water mass boundaries in the region. High species turnover occurred at depths <1200 m, and may be driven by changes in water mass characteristics including temperature (4.8–24.4 °C) and dissolved oxygen (2.2–9.5 mg per l). Our study suggests the importance of water masses in influencing community structure of benthic fauna, while considerably adding to the knowledge of mesophotic and deep-sea fish biogeography.Funding was provided by NOAA-OER for the 2014 E/V Nautilus cruise and by the USGS Environments and Hazards Program and Ocean Exploration Trust for the 2013 E/V Nautilus 807 cruise.2019-03-1
Quantifying methane point sources from fine-scale satellite observations of atmospheric methane plumes
Anthropogenic methane emissions originate from a large
number of relatively small point sources. The planned GHGSat satellite fleet
aims to quantify emissions from individual point sources by measuring methane
column plumes over selected ∼ 10×10 km2 domains with
 ≤ 50×50 m2 pixel resolution and 1 %–5 %
measurement precision. Here we develop algorithms for retrieving point source
rates from such measurements. We simulate a large ensemble of instantaneous
methane column plumes at 50×50 m2 pixel resolution for a range
of atmospheric conditions using the Weather Research and Forecasting model
(WRF) in large eddy simulation (LES) mode and adding instrument noise. We
show that standard methods to infer source rates by Gaussian plume inversion
or source pixel mass balance are prone to large errors because the turbulence
cannot be properly parameterized on the small scale of instantaneous methane
plumes. The integrated mass enhancement (IME) method, which relates total
plume mass to source rate, and the cross-sectional flux method, which infers
source rate from fluxes across plume transects, are better adapted to the
problem. We show that the IME method with local measurements of
the 10 m wind speed can infer source rates with an error of
0.07–0.17 t h−1 + 5 %–12 % depending on instrument precision
(1 %–5 %). The cross-sectional flux method has slightly larger
errors (0.07–0.26 t h−1 + 8 %–12 %) but a simpler physical
basis. For comparison, point sources larger than 0.3 t h−1 contribute
more than 75 % of methane emissions reported to the US Greenhouse Gas
Reporting Program. Additional error applies if local wind speed measurements
are not available and may dominate the overall error at low wind speeds. Low
winds are beneficial for source detection but detrimental for source
quantification.</p
Treatment of von Willebrand disease
Summary. von Willebrand disease is the most frequent of inherited bleeding disorders (1:100 affected individuals in the general population). The aim of treatment is to correct the dual defects of haemostasis, i.e., abnormal coagulation expressed by low levels of factor VIII and abnormal platelet adhesion expressed by a prolonged bleeding time. There are two main options available for the management of von Willebrand disease: desmopressin and transfusion therapy with blood products. Desmopressin is the treatment of choice in patients with type 1 von Willebrand disease, who account for approximately 80% of cases. This pharmacological compound raises endogenous factor VIII and von Willebrand factors and thereby corrects the intrinsic coagulation defect and the prolonged bleeding time in most type 1 patients. In type 3 and in the majority of type 2 patients desmopressin is not effective, and it is necessary to resort to plasma concentrates containing factor VIII and von Willebrand factor. Treated with virucidal methods, these concentrates are effective and currently safe, but the bleeding time defect is not always corrected by them. Platelet concentrates or desmopressin can be used as adjunctive treatments when poor correction of the bleeding time after concentrates is associated with continued bleeding
On the 'centre of gravity' method for measuring the composition of magnetite/maghemite mixtures, or the stoichiometry of magnetite-maghemite solid solutions, via Fe-57 Mossbauer spectroscopy
We evaluate the application of 57Fe Mössbauer spectroscopy to the determination of the
composition of magnetite (Fe3O4)/maghemite (γ-Fe2O3) mixtures and the stoichiometry
of magnetite-maghemite solid solutions. In particular, we consider a recently proposed
model-independent method which does not rely on a priori assumptions regarding the
nature of the sample, other than that it is free of other Fe-containing phases. In it a single
parameter, δRT—the ‘centre of gravity’, or area weighted mean isomer shift at room
temperature, T = 295 ± 5 K—is extracted by curve-fitting a sample’s Mössbauer spectrum,
and is correlated to the sample’s composition or stoichiometry. We present data on highpurity
magnetite and maghemite powders, and mixtures thereof, as well as comparison
literature data from nanoparticulate mixtures and solid solutions, to show that a linear
correlation exists between δRT and the numerical proportion of Fe atoms in the magnetite
environment: α = Femagnetite/Fetotal = − ( ) δ δ RT o /m, where δo = 0.3206 ± 0.0022mm s−1
and m = 0.2135 ± 0.0076mm s−1
. We also present equations to relate α to the weight
percentage w of magnetite in mixed phases, and the magnetite stoichiometry x = Fe2+/Fe3+
in solid solutions. The analytical method is generally applicable, but is most accurate when
the absorption profiles are sharp; in some samples this may require spectra to be recorded
at reduced temperatures. We consider such cases and provide equations to relate δ ( ) T to the
corresponding α value
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