We introduce a method convolutional neural networks to detect the presence of clouds in airborne camera images. We quantify the performance of this Cloud Detection Neural Network (CDNN) using ...human-labeled validation data where we report a 96% accuracy in detecting clouds in testing datasets for both Zenith- viewing and Forward-viewing models. We assess our performance by comparing the flight-averaged cloud fraction of zenith and forward CDNN retrievals, with that of the prototype hyperspectral total-diffuse Sunshine Pyranometer (SPN-S) instrument’s cloud optical depth data. Comparison of the CDNN with the SPN-S on time specific intervals resulted in 93% accuracy for the zenith- viewing CDNN and 84% for the forward- viewing CDNN. The comparison of the CDNNs with the SPN-S on flight-averaged cloud fraction resulted in an agreement of 0.15 for the Forward CDNN and 0.07 for the Zenith CDNN. We then quantify the ability of the CDNN to identify the presence of clouds above the aircraft using a forward- looking camera mounted inside the aircraft cockpit compared to the use of an All- Sky upward-looking camera that is mounted outside the fuselage on top of the aircraft. We present results from the CDNN based on airborne imagery from the NASA Aerosol Cloud Meteorology Interactions Over the Western Atlantic Experiment (ACTIVATE) and the Clouds, Aerosol and Monsoon Processes- Philippines Experiment (CAMP2Ex). For CAMP2Ex 53% of flight dates had above- aircraft cloud fraction above 50%, while for ACTIVATE 52% and 54% of flight dates observed above-aircraft cloud fraction above 50% for 2020 and 2021, respectively.
Differing boundary/mixed-layer height measurement methods were assessed in moderately-polluted and clean environments, with a focus on the Vaisala CL51 ceilometer. This intercomparison was performed ...as part of ongoing measurements at the Chemistry And Physics of the Atmospheric Boundary Layer Experiment (CAPABLE) site in Hampton, Virginia and during the 2014 Deriving Information on Surface Conditions from Column and Vertically Resolved Observations Relevant to Air Quality (DISCOVER-AQ) field campaign that took place in and around Denver, Colorado. We analyzed CL51 data that were collected via two different methods (BLView software, which applied correction factors, and simple terminal emulation logging) to determine the impact of data collection methodology. Further, we evaluated the STRucture of the ATmosphere (STRAT) algorithm as an open-source alternative to BLView (note that the current work presents an evaluation of the BLView and STRAT algorithms and does not intend to act as a validation of either). Filtering criteria were defined according to the change in mixed-layer height (MLH) distributions for each instrument and algorithm and were applied throughout the analysis to remove high-frequency fluctuations from the MLH retrievals. Of primary interest was determining how the different data-collection methodologies and algorithms compare to each other and to radiosonde-derived boundary-layer heights when deployed as part of a larger instrument network. We determined that data-collection methodology is not as important as the processing algorithm and that much of the algorithm differences might be driven by impacts of local meteorology and precipitation events that pose algorithm difficulties. The results of this study show that a common processing algorithm is necessary for LIght Detection And Ranging (LIDAR)-based MLH intercomparisons, and ceilometer-network operation and that sonde-derived boundary layer heights are higher (10-15% at mid-day) than LIDAR-derived mixed-layer heights. We show that averaging the retrieved MLH to 1-hour resolution (an appropriate time scale for a priori data model initialization) significantly improved correlation between differing instruments and differing algorithms.
ARCTIC RADIATION-ICEBRIDGE SEA AND ICE EXPERIMENT Smith, William L.; Hansen, Christy; Bucholtz, Anthony ...
Bulletin of the American Meteorological Society,
07/2017, Volume:
98, Issue:
7
Journal Article
Peer reviewed
Open access
The National Aeronautics and Space Administration (NASA)’s Arctic Radiation-IceBridge Sea and Ice Experiment (ARISE) acquired unique aircraft data on atmospheric radiation and sea ice properties ...during the critical late summer to autumn sea ice minimum and commencement of refreezing. The C-130 aircraft flew 15 missions over the Beaufort Sea between 4 and 24 September 2014. ARISE deployed a shortwave and longwave broadband radiometer (BBR) system from the Naval Research Laboratory; a Solar Spectral Flux Radiometer (SSFR) from the University of Colorado Boulder; the Spectrometer for Sky-Scanning, Sun-Tracking Atmospheric Research (4STAR) from the NASA Ames Research Center; cloud microprobes from the NASA Langley Research Center; and the Land, Vegetation and Ice Sensor (LVIS) laser altimeter system from the NASA Goddard Space Flight Center. These instruments sampled the radiant energy exchange between clouds and a variety of sea ice scenarios, including prior to and after refreezing began. The most critical and unique aspect of ARISE mission planning was to coordinate the flight tracks with NASA Cloud and the Earth’s Radiant Energy System (CERES) satellite sensor observations in such a way that satellite sensor angular dependence models and derived top-of-atmosphere fluxes could be validated against the aircraft data over large gridbox domains of order 100–200 km. This was accomplished over open ocean, over the marginal ice zone (MIZ), and over a region of heavy sea ice concentration, in cloudy and clear skies. ARISE data will be valuable to the community for providing better interpretation of satellite energy budget measurements in the Arctic and for process studies involving ice–cloud–atmosphere energy exchange during the sea ice transition period.
The NASA Aerosol Cloud meTeorology Interactions oVer the western ATlantic Experiment (ACTIVATE) produced a unique dataset for research into aerosol–cloud–meteorology interactions, with applications ...extending from process-based studies to multi-scale model intercomparison and improvement as well as to remote-sensing algorithm assessments and advancements. ACTIVATE used two NASA Langley Research Center aircraft, a HU-25 Falcon and King Air, to conduct systematic and spatially coordinated flights over the northwest Atlantic Ocean, resulting in 162 joint flights and 17 other single-aircraft flights between 2020 and 2022 across all seasons. Data cover 574 and 592 cumulative flights hours for the HU-25 Falcon and King Air, respectively. The HU-25 Falcon conducted profiling at different level legs below, in, and just above boundary layer clouds (< 3 km) and obtained in situ measurements of trace gases, aerosol particles, clouds, and atmospheric state parameters. Under cloud-free conditions, the HU-25 Falcon similarly conducted profiling at different level legs within and immediately above the boundary layer. The King Air (the high-flying aircraft) flew at approximately ∼ 9 km and conducted remote sensing with a lidar and polarimeter while also launching dropsondes (785 in total). Collectively, simultaneous data from both aircraft help to characterize the same vertical column of the atmosphere. In addition to individual instrument files, data from the HU-25 Falcon aircraft are combined into “merge files” on the publicly available data archive that are created at different time resolutions of interest (e.g., 1, 5, 10, 15, 30, 60 s, or matching an individual data product's start and stop times). This paper describes the ACTIVATE flight strategy, instrument and complementary dataset products, data access and usage details, and data application notes. The data are publicly accessible through https://doi.org/10.5067/SUBORBITAL/ACTIVATE/DATA001 (ACTIVATE Science Team, 2020).
The National Aeronautics and Space Administration (NASA)’s Arctic Radiation-IceBridge Sea and Ice Experiment (ARISE) acquired unique aircraft data on atmospheric radiation and sea ice properties ...during the critical late summer to autumn sea ice minimum and commencement of refreezing. The C-130 aircraft flew 15 missions over the Beaufort Sea between 4 and 24 September 2014. ARISE deployed a shortwave and longwave broadband radiometer (BBR) system from the Naval Research Laboratory; a Solar Spectral Flux Radiometer (SSFR) from the University of Colorado Boulder; the Spectrometer for Sky-Scanning, Sun-Tracking Atmospheric Research (4STAR) from the NASA Ames Research Center; cloud microprobes from the NASA Langley Research Center; and the Land, Vegetation and Ice Sensor (LVIS) laser altimeter system from the NASA Goddard Space Flight Center. These instruments sampled the radiant energy exchange between clouds and a variety of sea ice scenarios, including prior to and after refreezing began. The most critical and unique aspect of ARISE mission planning was to coordinate the flight tracks with NASA Cloud and the Earth’s Radiant Energy System (CERES) satellite sensor observations in such a way that satellite sensor angular dependence models and derived top-of-atmosphere fluxes could be validated against the aircraft data over large gridbox domains of order 100-200 km. This was accomplished over open ocean, over the marginal ice zone (MIZ), and over a region of heavy sea ice concentration, in cloudy and clear skies. ARISE data will be valuable to the community for providing better interpretation of satellite energy budget measurements in the Arctic and for process studies involving ice-cloud-atmosphere energy exchange during the sea ice transition period.
A Framework for Testing RESTful Web Services Reza, Hassan; Van Gilst, David
2010 Seventh International Conference on Information Technology: New Generations,
2010-April
Conference Proceeding
While web services greatly reduce the cost and complexity of integrating systems; they also introduce a number of additional challenges for testing because web services require standards, API, ...communication protocols and architecture that are not fully supported by traditional software testing methods and tools. In this paper, we discuss a software framework for providing a variety of test inputs for web service depended software, including predetermined test cases, replay of previous data, and generation of random test cases through data perturbation from a provided template.
BACKGROUND:To quantify the association between effects of interventions on carotid intima-media thickness (cIMT) progression and their effects on cardiovascular disease (CVD) risk.
METHODS:We ...systematically collated data from randomized, controlled trials. cIMT was assessed as the mean value at the common-carotid-artery; if unavailable, the maximum value at the common-carotid-artery or other cIMT measures were used. The primary outcome was a combined CVD end point defined as myocardial infarction, stroke, revascularization procedures, or fatal CVD. We estimated intervention effects on cIMT progression and incident CVD for each trial, before relating the 2 using a Bayesian meta-regression approach.
RESULTS:We analyzed data of 119 randomized, controlled trials involving 100 667 patients (mean age 62 years, 42% female). Over an average follow-up of 3.7 years, 12 038 patients developed the combined CVD end point. Across all interventions, each 10 μm/y reduction of cIMT progression resulted in a relative risk for CVD of 0.91 (95% Credible Interval, 0.87–0.94), with an additional relative risk for CVD of 0.92 (0.87–0.97) being achieved independent of cIMT progression. Taken together, we estimated that interventions reducing cIMT progression by 10, 20, 30, or 40 μm/y would yield relative risks of 0.84 (0.75–0.93), 0.76 (0.67–0.85), 0.69 (0.59–0.79), or 0.63 (0.52–0.74), respectively. Results were similar when grouping trials by type of intervention, time of conduct, time to ultrasound follow-up, availability of individual-participant data, primary versus secondary prevention trials, type of cIMT measurement, and proportion of female patients.
CONCLUSIONS:The extent of intervention effects on cIMT progression predicted the degree of CVD risk reduction. This provides a missing link supporting the usefulness of cIMT progression as a surrogate marker for CVD risk in clinical trials.
Aims
While heart failure with preserved (HFpEF) and reduced ejection fraction (HFrEF) are well described, determinants and outcomes of heart failure with mid‐range ejection fraction (HFmrEF) remain ...unclear. We sought to examine clinical and biochemical predictors of incident HFmrEF in the community.
Methods and results
We pooled data from four community‐based longitudinal cohorts, with ascertainment of new heart failure (HF) classified into HFmrEF ejection fraction (EF) 41–49%, HFpEF (EF ≥50%), and HFrEF (EF ≤40%). Predictors of incident HF subtypes were assessed using multivariable Cox models. Among 28 820 participants free of HF followed for a median of 12 years, there were 200 new HFmrEF cases, compared with 811 HFpEF and 1048 HFrEF. Clinical predictors of HFmrEF included age, male sex, systolic blood pressure, diabetes mellitus, and prior myocardial infarction (multivariable adjusted P ≤ 0.003 for all). Biomarkers that predicted HFmrEF included natriuretic peptides, cystatin‐C, and high‐sensitivity troponin (P ≤ 0.0004 for all). Natriuretic peptides were stronger predictors of HFrEF hazard ratio (HR) 2.00 per 1 standard deviation increase, 95% confidence interval (CI) 1.81–2.20 than of HFmrEF (HR 1.51, 95% CI 1.20–1.90, P = 0.01 for difference), and did not differ in their association with incident HFmrEF and HFpEF (HR 1.56, 95% CI 1.41–1.73, P = 0.68 for difference). All‐cause mortality following the onset of HFmrEF was worse than that of HFpEF (50 vs. 39 events per 1000 person‐years, P = 0.02), but comparable to that of HFrEF (46 events per 1000 person‐years, P = 0.78).
Conclusions
We found overlap in predictors of incident HFmrEF with other HF subtypes. In contrast, mortality risk after HFmrEF was worse than HFpEF, and similar to HFrEF.
Early after coronary artery bypass surgery (CABG), activation of numerous neurohumoral and endogenous vasodilator systems occurs that could be influenced favorably by angiotensin-converting enzyme ...inhibitors.
The Ischemia Management with Accupril post-bypass Graft via Inhibition of the coNverting Enzyme (IMAGINE) trial tested whether early initiation (< or = 7 days) of an angiotensin-converting enzyme inhibitor after CABG reduced cardiovascular events in stable patients with left ventricular ejection fraction > or = 40%. The trial was a double-blind, placebo-controlled study of 2553 patients randomly assigned to quinapril, target dose 40 mg/d, or placebo, who were followed up to a maximum of 43 months. The mean (SD) age was 61 (10) years. The incidence of the primary composite end point (cardiovascular death, resuscitated cardiac arrest, nonfatal myocardial infarction, coronary revascularization, unstable angina or heart failure requiring hospitalization, documented angina, and stroke) was 13.7% in the quinapril group and 12.2% in the placebo group (hazard ratio 1.15, 95% confidence interval 0.92 to 1.42, P=0.212) over a median follow-up of 2.95 years. The incidence of the primary composite end point increased significantly in the first 3 months after CABG in the quinapril group (hazard ratio 1.52, 95% confidence interval 1.03 to 2.26, P=0.0356). Adverse events also increased in the quinapril group, particularly during the first 3 months after CABG.
In patients at low risk of cardiovascular events after CABG, routine early initiation of angiotensin-converting enzyme inhibitor therapy does not appear to improve clinical outcome up to 3 years after CABG; however, it increases the incidence of adverse events, particularly early after CABG. Thus, early after CABG, initiation of angiotensin-converting enzyme inhibitor therapy should be individualized and continually reassessed over time according to risk.
Nearly half of all patients with heart failure have preserved ejection fraction (HFpEF) as opposed to reduced ejection fraction (HFrEF), yet associations of biomarkers with future heart failure ...subtype are incompletely understood.
To evaluate the associations of 12 cardiovascular biomarkers with incident HFpEF vs HFrEF among adults from the general population.
This study included 4 longitudinal community-based cohorts: the Cardiovascular Health Study (1989-1990; 1992-1993 for supplemental African-American cohort), the Framingham Heart Study (1995-1998), the Multi-Ethnic Study of Atherosclerosis (2000-2002), and the Prevention of Renal and Vascular End-stage Disease study (1997-1998). Each cohort had prospective ascertainment of incident HFpEF and HFrEF. Data analysis was performed from June 25, 2015, to November 9, 2017.
The following biomarkers were examined: N-terminal pro B-type natriuretic peptide or brain natriuretic peptide, high-sensitivity troponin T or I, C-reactive protein (CRP), urinary albumin to creatinine ratio (UACR), renin to aldosterone ratio, D-dimer, fibrinogen, soluble suppressor of tumorigenicity, galectin-3, cystatin C, plasminogen activator inhibitor 1, and interleukin 6.
Development of incident HFpEF and incident HFrEF.
Among the 22 756 participants in these 4 cohorts (12 087 women and 10 669 men; mean SD age, 60 13 years) in the study, during a median follow-up of 12 years, 633 participants developed incident HFpEF, and 841 developed HFrEF. In models adjusted for clinical risk factors of heart failure, 2 biomarkers were significantly associated with incident HFpEF: UACR (hazard ratio HR, 1.33; 95% CI, 1.20-1.48; P < .001) and natriuretic peptides (HR, 1.27; 95% CI, 1.16-1.40; P < .001), with suggestive associations for high-sensitivity troponin (HR, 1.11; 95% CI, 1.03-1.19; P = .008), plasminogen activator inhibitor 1 (HR, 1.22; 95% CI, 1.03-1.45; P = .02), and fibrinogen (HR, 1.12; 95% CI, 1.03-1.22; P = .01). By contrast, 6 biomarkers were associated with incident HFrEF: natriuretic peptides (HR, 1.54; 95% CI, 1.41-1.68; P < .001), UACR (HR, 1.21; 95% CI, 1.11-1.32; P < .001), high-sensitivity troponin (HR, 1.37; 95% CI, 1.29-1.46; P < .001), cystatin C (HR, 1.19; 95% CI, 1.11-1.27; P < .001), D-dimer (HR, 1.22; 95% CI, 1.11-1.35; P < .001), and CRP (HR, 1.19; 95% CI, 1.11-1.28; P < .001). When directly compared, natriuretic peptides, high-sensitivity troponin, and CRP were more strongly associated with HFrEF compared with HFpEF.
Biomarkers of renal dysfunction, endothelial dysfunction, and inflammation were associated with incident HFrEF. By contrast, only natriuretic peptides and UACR were associated with HFpEF. These findings highlight the need for future studies focused on identifying novel biomarkers of the risk of HFpEF.
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