127 research outputs found
Rockfall Magnitude-Frequency Relationship Based on Multi-Source Data from Monitoring and Inventory
Quantitative hazard analysis of rockfalls is a fundamental tool for sustainable risk management, even more so in places where the preservation of natural heritage and people's safety must find the right balance. The first step consists in determining the magnitude-frequency relationship, which corresponds to the apparently simple question: how big and how often will a rockfall be detached from anywhere in the cliff? However, there is usually only scarce data on past activity from which to derive a quantitative answer. Methods are proposed to optimize the exploitation of multi-source inventories, introducing sampling extent as a main attribute for the analysis. This work explores the maximum possible synergy between data sources as different as traditional inventories of observed events and current remote sensing techniques. Both information sources may converge, providing complementary results in the magnitude-frequency relationship, taking advantage of each strength that overcomes the correspondent weakness. Results allow characterizing rockfall detachment hazardous conditions and reveal many of the underlying conditioning factors, which are analyzed in this paper. High variability of the hazard over time and space has been found, with strong dependencies on influential external factors. Therefore, it will be necessary to give the appropriate reading to the magnitude-frequency scenarios, depending on the application of risk management tools (e.g., hazard zoning, quantitative risk analysis, or actions that bring us closer to its forecast). In this sense, some criteria and proxies for hazard assessment are proposed in the paper
Machine Learning-Based Rockfalls Detection with 3D Point Clouds, Example in the Montserrat Massif (Spain)
Rock slope monitoring using 3D point cloud data allows the creation of rockfall inventories, provided that an efficient methodology is available to quantify the activity. However, monitoring with high temporal and spatial resolution entails the processing of a great volume of data, which can become a problem for the processing system. The standard methodology for monitoring includes the steps of data capture, point cloud alignment, the measure of differences, clustering differences, and identification of rockfalls. In this article, we propose a new methodology adapted from existing algorithms (multiscale model to model cloud comparison and density-based spatial clustering of applications with noise algorithm) and machine learning techniques to facilitate the identification of rockfalls from compared temporary 3D point clouds, possibly the step with most user interpretation. Point clouds are processed to generate 33 new features related to the rock cliff differences, predominant differences, or orientation for classification with 11 machine learning models, combined with 2 undersampling and 13 oversampling methods. The proposed methodology is divided into two software packages: point cloud monitoring and cluster classification. The prediction model applied in two study cases in the Montserrat conglomeratic massif (Barcelona, Spain) reveal that a reduction of 98% in the initial number of clusters is sufficient to identify the totality of rockfalls in the first case study. The second case study requires a 96% reduction to identify 90% of the rockfalls, suggesting that the homogeneity of the rockfall characteristics is a key factor for the correct prediction of the machine learning models
Serum Potassium Dynamics During Acute Heart Failure Hospitalization
[Abstract]
Background.
Available information about prognostic implications of potassium levels alteration in the setting of acute heart failure (AHF) is scarce.
Objectives.
We aim to describe the prevalence of dyskalemia (hypo or hyperkalemia), its dynamic changes during AHF-hospitalization, and its long-term clinical impact after hospitalization.
Methods.
We analyzed 1779 patients hospitalized with AHF who were included in the REDINSCOR II registry. Patients were classified in three groups, according to potassium levels both on admission and discharge: hypokalemia (potassiumââ5 mEq/L).
Results.
The prevalence of hypokalemia and hyperkalemia on admission was 8.2 and 4.6%, respectively, and 6.4 and 2.7% at discharge. Hyperkalemia on admission was associated with higher in-hospital mortality (ORâ=â2.32 [95% CI: 1.04â5.21] pâ=â0.045). Among patients with hypokalemia on admission, 79% had normalized potassium levels at discharge. In the case of patients with hyperkalemia on admission, 89% normalized kalemia before discharge. In multivariate Cox regression, dyskalemia was associated with higher 12-month mortality, (HRâ=â1.48 [95% CI, 1.12â1.96], pâ=â0.005). Among all patterns of dyskalemia persistent hypokalemia (HRâ=â3.17 [95% CI: 1.71â5.88]; pâ<â0.001), and transient hyperkalemia (HRâ=â1.75 [95% CI: 1.07â2.86]; pâ=â0.023) were related to reduced 12-month survival.
Conclusions.
Potassium levels alterations are frequent and show a dynamic behavior during AHF admission. Hyperkalemia on admission is an independent predictor of higher in-hospital mortality. Furthermore, persistent hypokalemia and transient hyperkalemia on admission are independent predictors of 12-month mortality.This work is funded by the Instituto de Salud Carlos III (Ministry of Economy, Industry, and Competitiveness) and co-funded by the European Regional Development Fund, through the CIBER in cardiovascular diseases (CB16/11/00502)
Short- and Long-Term Prognosis of Patients With Takotsubo Syndrome Based on Different Triggers: Importance of the Physical Nature
Background
Takotsubo syndrome (TTS) is an acute reversible heart condition initially believed to represent a benign pathology attributable to its self-limiting clinical course; however, little is known about its prognosis based on different triggers. This study compared short- and long-term outcomes between TTS based on different triggers, focusing on various physical triggering events.
Methods and Results
We analyzed patients with a definitive TTS diagnosis recruited for the Spanish National Registry on TTS (RETAKO [Registry on Takotsubo Syndrome]). Short- and long-term outcomes were compared between different groups according to triggering factors. A total of 939 patients were included. An emotional trigger was detected in 340 patients (36.2%), a physical trigger in 293 patients (31.2%), and none could be identified in 306 patients (32.6%). The main physical triggers observed were infections (30.7%), followed by surgical procedures (22.5%), physical activities (18.4%), episodes of severe hypoxia (18.4%), and neurological events (9.9%). TTS triggered by physical factors showed higher mortality in the short and long term, and within this group, patients whose physical trigger was hypoxia were those who had a worse prognosis, in addition to being triggered by physical factors, including age >70 years, diabetes mellitus, left ventricular eyection fraction <30% and shock on admission, and increased long-term mortality risk.
Conclusions
TTS triggered by physical factors could present a worse prognosis in terms of mortality. Under the TTS label, there could be as yet undiscovered very different clinical profiles, whose differentiation could lead to individual better management, and therefore the perception of TTS as having a benign prognosis should be generally ruled out
<i>Gaia</i> Data Release 1. Summary of the astrometric, photometric, and survey properties
Context. At about 1000 days after the launch of Gaia we present the first Gaia data release, Gaia DR1, consisting of astrometry and photometry for over 1 billion sources brighter than magnitude 20.7.
Aims. A summary of Gaia DR1 is presented along with illustrations of the scientific quality of the data, followed by a discussion of the limitations due to the preliminary nature of this release.
Methods. The raw data collected by Gaia during the first 14 months of the mission have been processed by the Gaia Data Processing and Analysis Consortium (DPAC) and turned into an astrometric and photometric catalogue.
Results. Gaia DR1 consists of three components: a primary astrometric data set which contains the positions, parallaxes, and mean proper motions for about 2 million of the brightest stars in common with the HIPPARCOS and Tycho-2 catalogues â a realisation of the Tycho-Gaia Astrometric Solution (TGAS) â and a secondary astrometric data set containing the positions for an additional 1.1 billion sources. The second component is the photometric data set, consisting of mean G-band magnitudes for all sources. The G-band light curves and the characteristics of âŒ3000 Cepheid and RR-Lyrae stars, observed at high cadence around the south ecliptic pole, form the third component. For the primary astrometric data set the typical uncertainty is about 0.3 mas for the positions and parallaxes, and about 1 mas yrâ1 for the proper motions. A systematic component of âŒ0.3 mas should be added to the parallax uncertainties. For the subset of âŒ94 000 HIPPARCOS stars in the primary data set, the proper motions are much more precise at about 0.06 mas yrâ1. For the secondary astrometric data set, the typical uncertainty of the positions is âŒ10 mas. The median uncertainties on the mean G-band magnitudes range from the mmag level to âŒ0.03 mag over the magnitude range 5 to 20.7.
Conclusions. Gaia DR1 is an important milestone ahead of the next Gaia data release, which will feature five-parameter astrometry for all sources. Extensive validation shows that Gaia DR1 represents a major advance in the mapping of the heavens and the availability of basic stellar data that underpin observational astrophysics. Nevertheless, the very preliminary nature of this first Gaia data release does lead to a number of important limitations to the data quality which should be carefully considered before drawing conclusions from the data
Improving the biopharmaceutical attributes of mangiferin using vitamin E-TPGS co-loaded self-assembled phosholipidic nano-mixed micellar systems
The current research work encompasses the development, characterization, and evaluation of self-assembled phospholipidic nano-mixed miceller system (SPNMS) of a poorly soluble BCS Class IV xanthone bioactive, mangiferin (Mgf) functionalized with co-delivery of vitamin E TPGS. Systematic optimization using I-optimal design yielded self-assembled phospholipidic nano-micelles with a particle size of â80% of drug release in 15 min. The cytotoxicity and cellular uptake studies performed using MCF-7 and MDA-MB-231 cell lines demonstrated greater kill and faster cellular uptake. The ex vivo intestinal permeability revealed higher lymphatic uptake, while in situ perfusion and in vivo pharmacokinetic studies indicated nearly 6.6- and 3.0-folds augmentation in permeability and bioavailability of Mgf. In a nutshell, vitamin E functionalized SPNMS of Mgf improved the biopharmaceutical performance of Mgf in rats for enhanced anticancer potency
Gaia Data Release 1:The archive visualisation service
Context: The first Gaia data release (DR1) delivered a catalogue of
astrometry and photometry for over a billion astronomical sources. Within the
panoply of methods used for data exploration, visualisation is often the
starting point and even the guiding reference for scientific thought. However,
this is a volume of data that cannot be efficiently explored using traditional
tools, techniques, and habits.
Aims: We aim to provide a global visual exploration service for the Gaia
archive, something that is not possible out of the box for most people. The
service has two main goals. The first is to provide a software platform for
interactive visual exploration of the archive contents, using common personal
computers and mobile devices available to most users. The second aim is to
produce intelligible and appealing visual representations of the enormous
information content of the archive.
Methods: The interactive exploration service follows a client-server design.
The server runs close to the data, at the archive, and is responsible for
hiding as far as possible the complexity and volume of the Gaia data from the
client. This is achieved by serving visual detail on demand. Levels of detail
are pre-computed using data aggregation and subsampling techniques. For DR1,
the client is a web application that provides an interactive multi-panel
visualisation workspace as well as a graphical user interface.
Results: The Gaia archive Visualisation Service offers a web-based
multi-panel interactive visualisation desktop in a browser tab. It currently
provides highly configurable 1D histograms and 2D scatter plots of Gaia DR1 and
the Tycho-Gaia Astrometric Solution (TGAS) with linked views. An innovative
feature is the creation of ADQL queries from visually defined regions in plots.
[abridged]Comment: 16 pages, 9 figures, accepted for publication in Astronomy &
Astrophysics. Abstract abridged for arXiv submission. The service and image
gallery here described are accessible from the Gaia archive "visualization"
tab at http://gea.esac.esa.int/archive
Gaia Focused Product Release: Radial velocity time series of long-period variables
The third Gaia Data Release (DR3) provided photometric time series of more
than 2 million long-period variable (LPV) candidates. Anticipating the
publication of full radial-velocity (RV) in DR4, this Focused Product Release
(FPR) provides RV time series for a selection of LPVs with high-quality
observations. We describe the production and content of the Gaia catalog of LPV
RV time series, and the methods used to compute variability parameters
published in the Gaia FPR. Starting from the DR3 LPVs catalog, we applied
filters to construct a sample of sources with high-quality RV measurements. We
modeled their RV and photometric time series to derive their periods and
amplitudes, and further refined the sample by requiring compatibility between
the RV period and at least one of the , , or
photometric periods. The catalog includes RV time series and variability
parameters for 9\,614 sources in the magnitude range , including a flagged top-quality subsample of 6\,093 stars
whose RV periods are fully compatible with the values derived from the ,
, and photometric time series. The RV time series
contain a mean of 24 measurements per source taken unevenly over a duration of
about three years. We identify the great most sources (88%) as genuine LPVs,
with about half of them showing a pulsation period and the other half
displaying a long secondary period. The remaining 12% consists of candidate
ellipsoidal binaries. Quality checks against RVs available in the literature
show excellent agreement. We provide illustrative examples and cautionary
remarks. The publication of RV time series for almost 10\,000 LPVs constitutes,
by far, the largest such database available to date in the literature. The
availability of simultaneous photometric measurements gives a unique added
value to the Gaia catalog (abridged)Comment: 36 pages, 38 figure
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Gaia Early Data Release 3: The celestial reference frame (Gaia-CRF3)
Context. Gaia-CRF3 is the celestial reference frame for positions and proper motions in the third release of data from the Gaia mission, Gaia DR3 (and for the early third release, Gaia EDR3, which contains identical astrometric results). The reference frame is defined by the positions and proper motions at epoch 2016.0 for a specific set of extragalactic sources in the (E)DR3 catalogue. Aims. We describe the construction of Gaia-CRF3 and its properties in terms of the distributions in magnitude, colour, and astrometric quality. Methods. Compact extragalactic sources in Gaia DR3 were identified by positional cross-matching with 17 external catalogues of quasi-stellar objects (QSO) and active galactic nuclei (AGN), followed by astrometric filtering designed to remove stellar contaminants. Selecting a clean sample was favoured over including a higher number of extragalactic sources. For the final sample, the random and systematic errors in the proper motions are analysed, as well as the radio-optical offsets in position for sources in the third realisation of the International Celestial Reference Frame (ICRF3). Results. Gaia-CRF3 comprises about 1.6 million QSO-like sources, of which 1.2 million have five-parameter astrometric solutions in Gaia DR3 and 0.4 million have six-parameter solutions. The sources span the magnitude range G = 13-21 with a peak density at 20.6 mag, at which the typical positional uncertainty is about 1 mas. The proper motions show systematic errors on the level of 12 ÎŒas yr-1 on angular scales greater than 15 deg. For the 3142 optical counterparts of ICRF3 sources in the S/X frequency bands, the median offset from the radio positions is about 0.5 mas, but it exceeds 4 mas in either coordinate for 127 sources. We outline the future of Gaia-CRF in the next Gaia data releases. Appendices give further details on the external catalogues used, how to extract information about the Gaia-CRF3 sources, potential (Galactic) confusion sources, and the estimation of the spin and orientation of an astrometric solution
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