Endmember extraction algorithms from hyperspectral images

During the last years, several high-resolution sensors have been developed for hyperspectral remote sensing applications. Some of these sensors are already available on space-borne devices. Space-borne sensors are currently acquiring a continual stream of hyperspectral data, and new efficient unsupervised algorithms are required to analyze the great amount of data produced by these instruments. The identification of image endmembers is a crucial task in hyperspectral data exploitation. Once the individual endmembers have been identified, several methods can be used to map their spatial distribution, associations and abundances. This paper reviews the Pixel Purity Index (PPI), N-FINDR and Automatic Morphological Endmember Extraction (AMEE) algorithms developed to accomplish the task of finding appropriate image endmembers by applying them to real hyperspectral data. In order to compare the performance of these methods a metric based on the Root Mean Square Error (RMSE) between the estimated and reference abundance maps is used

Endmember extraction algorithms from hyperspectral images

During the last years, several high-resolution sensors have been developed for hyperspectral remote sensing applications. Some of these sensors are already available on space-borne devices. Space-borne sensors are currently acquiring a continual stream of hyperspectral data, and new efficient unsupervised algorithms are required to analyze the great amount of data produced by these instruments. The identification of image endmembers is a crucial task in hyperspectral data exploitation. Once the individual endmembers have been identified, several methods can be used to map their spatial distribution, associations and abundances. This paper reviews the Pixel Purity Index (PPI), N-FINDR and Automatic Morphological Endmember Extraction (AMEE) algorithms developed to accomplish the task of finding appropriate image endmembers by applying them to real hyperspectral data. In order to compare the performance of these methods a metric based on the Root Mean Square Error (RMSE) between the estimated and reference abundance maps is used

Social comparison processes and catastrophising in fibromyalgia:A path analysis

Introduction: In addition to coping strategies, social comparison may play a role in illness adjustment. However, little is known about the role of contrast and identification in social comparison in adaptation to fibromyalgia.Aim: To evaluate through a path analysis in a sample of fibromyalgia patients, the association between identification and contrast in social comparison, catastrophising and specific health outcomes (fibromyalgia illness impact and psychological distress).Material and Method: 131 Spanish fibromyalgia outpatients (mean age: 50.15, SD=11.1) filled out a questionnaire.Results: We present a model that explained 33% of the variance in catastrophising by direct effects of more use of upward contrast and downward identification. In addition, 35% of fibromyalgia illness impact variance was explained by less upward identification, more upward contrast and more catastrophising and 42% of the variance in psychological distress by a direct effect of more use of upward contrast together with higher fibromyalgia illness impact.Discussion: We suggest that intervention programmes with chronic pain and fibromyalgia patients should focus on enhancing the use of upward identification in social comparison, and on minimising the use of upward contrast and downward identification in social comparison

The Gaia white dwarf population within 100 pc of the Sun

The 21st European Workshop on White Dwarfs was held in Austin, TX from July 23rd to 27th of 2018The recent Gaia Data Release 2 has provided an unprecedented sample of the local white dwarf population. The high astrometric resolution and the photometry provided by Gaia allows to build a clean magnitude-color diagram that, with the aid of the most updated population synthesis simulator, permit us to select the sample of white dwarf candidates. Our analysis shows that Gaia has virtually identified all white dwarfs within 100 pc from the Sun. Additionally, we use the Virtual Observatory tool VOSA to derive effective temperatures and luminosities for our sources by fitting their spectral energy distributions. The Gaia 100 pc white dwarf population is clearly dominated by cool (~8,000 K) objects and reveals a significant population of massive (M ~ 0:8M ) white dwarfs, of which no more than ~30 - 40% can be attributed to hydrogen-deficient atmospheres. Preliminary results including white dwarf mergers seem not to explain this excess unless some ad hoc hypothesis are adopted. Finally, we use an Intelligent Artificial algorithm based on the Random Forest method to disentangle the different Galactic components of the white dwarf population. Our results show that the thin, thick and halo ratio in the 100 pc sample is 89:11:1, identifying 97 halo white dwarf candidates.Astronom

CMV matrices in random matrix theory and integrable systems: a survey

We present a survey of recent results concerning a remarkable class of unitary matrices, the CMV matrices. We are particularly interested in the role they play in the theory of random matrices and integrable systems. Throughout the paper we also emphasize the analogies and connections to Jacobi matrices.Comment: Based on a talk given at the Short Program on Random Matrices, Random Processes and Integrable Systems, CRM, Universite de Montreal, 200

Exoplanet Imaging Data Challenge, phase II: Characterization of exoplanet signals in high-contrast images

Today, there exists a wide variety of algorithms dedicated to high-contrast imaging, especially for the detection and characterisation of exoplanet signals. These algorithms are tailored to address the very high contrast between the exoplanet signal(s), which can be more than two orders of magnitude fainter than the bright starlight residuals in coronagraphic images. The starlight residuals are inhomogeneously distributed and follow various timescales that depend on the observing conditions and on the target star brightness. Disentangling the exoplanet signals within the starlight residuals is therefore challenging, and new post-processing algorithms are striving to achieve more accurate astrophysical results. The Exoplanet Imaging Data Challenge is a community-wide effort to develop, compare and evaluate algorithms using a set of benchmark high-contrast imaging datasets. After a first phase ran in 2020 and focused on the detection capabilities of existing algorithms, the focus of this ongoing second phase is to compare the characterisation capabilities of state-of-the-art techniques. The characterisation of planetary companions is two-fold: the astrometry (estimated position with respect to the host star) and spectrophotometry (estimated contrast with respect to the host star, as a function of wavelength). The goal of this second phase is to offer a platform for the community to benchmark techniques in a fair, homogeneous and robust way, and to foster collaborations.Comment: Submitted to SPIE Astronomical Telescopes + Instrumentation 2022, Adaptive Optics Systems VIII, Paper 12185-

Antimicrobial use in European acute care hospitals: results from the second point prevalence survey (PPS) of healthcare-associated infections and antimicrobial use, 2016 to 2017

Antimicrobial agents used to treat infections are life-saving. Overuse may result in more frequent adverse effects and emergence of multidrug-resistant microorganisms. In 2016-17, we performed the second point-prevalence survey (PPS) of healthcare-associated infections (HAIs) and antimicrobial use in European acute care hospitals. We included 1,209 hospitals and 310,755 patients in 28 of 31 European Union/European Economic Area (EU/EEA) countries. The weighted prevalence of antimicrobial use in the EU/EEA was 30.5% (95% CI: 29.2-31.9%). The most common indication for prescribing antimicrobials was treatment of a community-acquired infection, followed by treatment of HAI and surgical prophylaxis. Over half (54.2%) of antimicrobials for surgical prophylaxis were prescribed for more than 1 day. The most common infections treated by antimicrobials were respiratory tract infections and the most commonly prescribed antimicrobial agents were penicillins with beta-lactamase inhibitors. There was wide variation of patients on antimicrobials, in the selection of antimicrobial agents and in antimicrobial stewardship resources and activities across the participating countries. The results of the PPS provide detailed information on antimicrobial use in European acute care hospitals, enable comparisons between countries and hospitals, and highlight key areas for national and European action that will support efforts towards prudent use of antimicrobials

High-carotenoid maize: development of plant biotechnology prototypes for human and animal health and nutrition

Carolight (R) is a transgenic maize variety that accumulates extraordinary levels of carotenoids, including those with vitamin A activity. The development of Carolight (R) maize involved the technical implementation of a novel combinatorial transformation method, followed by rigorous testing for transgene expression and the accumulation of different carotenoid molecules. Carolight (R) was envisaged as a way to improve the nutritional health of human populations that cannot access a diverse diet, but this ultimate humanitarian application can only be achieved after extensive testing for safety, agronomic performance and nutritional sufficiency. In this article, we chart the history of Carolight (R) maize focusing on its development, extensive field testing for agronomic performance and resistance to pests and pathogens, and feeding trials to analyze its impact on farm animals (and their meat/dairy products) as well as animal models of human diseases. We also describe more advanced versions of Carolight (R) endowed with pest-resistance traits, and other carotenoid-enhanced maize varieties originating from the same series of initial transformation experiments. Finally we discuss the further steps required before Carolight (R) can fulfil its humanitarian objectives, including the intellectual property and regulatory constraints that lie in its path

Hunt for new phenomena using large jet multiplicities and missing transverse momentum with ATLAS in 4.7 fb−1 of s√=7TeV proton-proton collisions

Results are presented of a search for new particles decaying to large numbers of jets in association with missing transverse momentum, using 4.7 fb−1 of pp collision data at s√=7TeV collected by the ATLAS experiment at the Large Hadron Collider in 2011. The event selection requires missing transverse momentum, no isolated electrons or muons, and from ≥6 to ≥9 jets. No evidence is found for physics beyond the Standard Model. The results are interpreted in the context of a MSUGRA/CMSSM supersymmetric model, where, for large universal scalar mass m 0, gluino masses smaller than 840 GeV are excluded at the 95% confidence level, extending previously published limits. Within a simplified model containing only a gluino octet and a neutralino, gluino masses smaller than 870 GeV are similarly excluded for neutralino masses below 100 GeV