492 research outputs found
Care coordination in two of Bogota’s public healthcare networks: A cross-sectional study among doctors
Introduction: Care coordination is a priority concern for healthcare systems. In Colombia, there is a lack of information on the topic. This study analysed how doctors of two Bogotá’s public healthcare networks perceived coordination between healthcare levels and what factors are associated with their perception. Methods: A cross-sectional study using the COORDENA-CO questionnaire to a sample of 363 doctors (network-1 = 181; network-2 = 182) in 2015. The questionnaire asks about types and dimensions of care coordination: information and clinical management, with items in a Likert scale, as well as conditions regarding health system, organisational and doctors’ conditions. Descriptive statistics and logistic regression analysis were performed. Results: The doctors’ perception of a high level of coordination did not exceed 25.4%. On coordination of information, limited transfer of clinical information was found. Concerning clinical management, there were limited care coherence, deficits in patient follow-up and lengthy waiting times for specialised care. A high perception of coordination were associated with being female, being over 50 years old, being a specialist, having less than one year’s working experience, working less than 20 h per week at the centre, forming part of network-1, having time available for performing coordination tasks, having job satisfaction and not identifying limitations imposed by healthcare insurers. Discussion: There was limited perception of coordination, in its different dimensions and types with some differences between networks. The results support the importance of guaranteeing job satisfaction, ensuring sufficient time to coordination-related activities and intervening in the restrictions imposed by healthcare insurers to improve care coordination. © The Author(s) 2019
Protist taxonomic and functional diversity in soil, freshwater and marine ecosystems
Protists dominate eukaryotic diversity and play key functional roles in all ecosystems, particularly by catalyzing carbon and nutrient cycling. To date, however, a comparative analysis of their taxonomic and functional diversity that compares the major ecosystems on Earth (soil, freshwater and marine systems) is missing. Here, we present a comparison of protist diversity based on standardized high throughput 18S rRNA gene sequencing of soil, freshwater and marine environmental DNA. Soil and freshwater protist communities were more similar to each other than to marine protist communities, with virtually no overlap of Operational Taxonomic Units (OTUs) between terrestrial and marine habitats. Soil protists showed higher γ diversity than aquatic samples. Differences in taxonomic composition of the communities led to changes in a functional diversity among ecosystems, as expressed in relative abundance of consumers, phototrophs and parasites. Phototrophs (eukaryotic algae) dominated freshwater systems (49% of the sequences) and consumers soil and marine ecosystems (59% and 48%, respectively). The individual functional groups were composed of ecosystem- specific taxonomic groups. Parasites were equally common in all ecosystems, yet, terrestrial systems hosted more OTUs assigned to parasites of macro-organisms while aquatic systems contained mostly microbial parasitoids. Together, we show biogeographic patterns of protist diversity across major ecosystems on Earth, preparing the way for more focused studies that will help understanding the multiple roles of protists in the biosphere
Modeling the Subsurface Structure of Sunspots
While sunspots are easily observed at the solar surface, determining their
subsurface structure is not trivial. There are two main hypotheses for the
subsurface structure of sunspots: the monolithic model and the cluster model.
Local helioseismology is the only means by which we can investigate
subphotospheric structure. However, as current linear inversion techniques do
not yet allow helioseismology to probe the internal structure with sufficient
confidence to distinguish between the monolith and cluster models, the
development of physically realistic sunspot models are a priority for
helioseismologists. This is because they are not only important indicators of
the variety of physical effects that may influence helioseismic inferences in
active regions, but they also enable detailed assessments of the validity of
helioseismic interpretations through numerical forward modeling. In this paper,
we provide a critical review of the existing sunspot models and an overview of
numerical methods employed to model wave propagation through model sunspots. We
then carry out an helioseismic analysis of the sunspot in Active Region 9787
and address the serious inconsistencies uncovered by
\citeauthor{gizonetal2009}~(\citeyear{gizonetal2009,gizonetal2009a}). We find
that this sunspot is most probably associated with a shallow, positive
wave-speed perturbation (unlike the traditional two-layer model) and that
travel-time measurements are consistent with a horizontal outflow in the
surrounding moat.Comment: 73 pages, 19 figures, accepted by Solar Physic
The exposure of the hybrid detector of the Pierre Auger Observatory
The Pierre Auger Observatory is a detector for ultra-high energy cosmic rays.
It consists of a surface array to measure secondary particles at ground level
and a fluorescence detector to measure the development of air showers in the
atmosphere above the array. The "hybrid" detection mode combines the
information from the two subsystems. We describe the determination of the
hybrid exposure for events observed by the fluorescence telescopes in
coincidence with at least one water-Cherenkov detector of the surface array. A
detailed knowledge of the time dependence of the detection operations is
crucial for an accurate evaluation of the exposure. We discuss the relevance of
monitoring data collected during operations, such as the status of the
fluorescence detector, background light and atmospheric conditions, that are
used in both simulation and reconstruction.Comment: Paper accepted by Astroparticle Physic
Evidence for a mixed mass composition at the `ankle' in the cosmic-ray spectrum
We report a first measurement for ultra-high energy cosmic rays of the
correlation between the depth of shower maximum and the signal in the water
Cherenkov stations of air-showers registered simultaneously by the fluorescence
and the surface detectors of the Pierre Auger Observatory. Such a correlation
measurement is a unique feature of a hybrid air-shower observatory with
sensitivity to both the electromagnetic and muonic components. It allows an
accurate determination of the spread of primary masses in the cosmic-ray flux.
Up till now, constraints on the spread of primary masses have been dominated by
systematic uncertainties. The present correlation measurement is not affected
by systematics in the measurement of the depth of shower maximum or the signal
in the water Cherenkov stations. The analysis relies on general characteristics
of air showers and is thus robust also with respect to uncertainties in
hadronic event generators. The observed correlation in the energy range around
the `ankle' at differs significantly from
expectations for pure primary cosmic-ray compositions. A light composition made
up of proton and helium only is equally inconsistent with observations. The
data are explained well by a mixed composition including nuclei with mass . Scenarios such as the proton dip model, with almost pure compositions, are
thus disfavoured as the sole explanation of the ultrahigh-energy cosmic-ray
flux at Earth.Comment: Published version. Added journal reference and DOI. Added Report
Numbe
A multi-species synthesis of physiological mechanisms in drought-induced tree mortality
Widespread tree mortality associated with drought 92 has been observed on all forested continents, and global change is expected to exacerbate vegetation vulnerability. Forest mortality has implications for future biosphere-atmosphere interactions of carbon, water, and energy balance, and is poorly represented in dynamic vegetation models. Reducing uncertainty requires improved mortality projections founded on robust physiological processes. However, the proposed mechanisms of drought-induced mortality, including hydraulic failure and carbon starvation, are unresolved. A growing number of empirical studies have investigated these mechanisms, but data have not been consistently analyzed across species and biomes using a standardized physiological framework. Here we show that xylem hydraulic failure was ubiquitous across multiple tree taxa at drought induced mortality. All species assessed had 60% or higher loss of xylem hydraulic conductivity, consistent with proposed theoretical and modelled survival thresholds. We found diverse responses in non-structural carbohydrate reserves at mortality, indicating that evidence supporting carbon starvation was not universal. Reduced non-structural carbohydrates were more common for gymnosperms than angiosperms, associated with xylem hydraulic vulnerability, and may have a role in reducing hydraulic function. Our finding that hydraulic failure at drought-induced mortality was persistent across species indicates that substantial improvement in vegetation modelling can be achieved using thresholds in hydraulic function
A multi-species synthesis of physiological mechanisms in drought-induced tree mortality
Widespread tree mortality associated with drought 92 has been observed on all forested continents, and global change is expected to exacerbate vegetation vulnerability. Forest mortality has implications for future biosphere-atmosphere interactions of carbon, water, and energy balance, and is poorly represented in dynamic vegetation models. Reducing uncertainty requires improved mortality projections founded on robust physiological processes. However, the proposed mechanisms of drought-induced mortality, including hydraulic failure and carbon starvation, are unresolved. A growing number of empirical studies have investigated these mechanisms, but data have not been consistently analyzed across species and biomes using a standardized physiological framework. Here we show that xylem hydraulic failure was ubiquitous across multiple tree taxa at drought induced mortality. All species assessed had 60% or higher loss of xylem hydraulic conductivity, consistent with proposed theoretical and modelled survival thresholds. We found diverse responses in non-structural carbohydrate reserves at mortality, indicating that evidence supporting carbon starvation was not universal. Reduced non-structural carbohydrates were more common for gymnosperms than angiosperms, associated with xylem hydraulic vulnerability, and may have a role in reducing hydraulic function. Our finding that hydraulic failure at drought-induced mortality was persistent across species indicates that substantial improvement in vegetation modelling can be achieved using thresholds in hydraulic function
Gap-filling eddy covariance methane fluxes:Comparison of machine learning model predictions and uncertainties at FLUXNET-CH4 wetlands
Time series of wetland methane fluxes measured by eddy covariance require gap-filling to estimate daily, seasonal, and annual emissions. Gap-filling methane fluxes is challenging because of high variability and complex responses to multiple drivers. To date, there is no widely established gap-filling standard for wetland methane fluxes, with regards both to the best model algorithms and predictors. This study synthesizes results of different gap-filling methods systematically applied at 17 wetland sites spanning boreal to tropical regions and including all major wetland classes and two rice paddies. Procedures are proposed for: 1) creating realistic artificial gap scenarios, 2) training and evaluating gap-filling models without overstating performance, and 3) predicting half-hourly methane fluxes and annual emissions with realistic uncertainty estimates. Performance is compared between a conventional method (marginal distribution sampling) and four machine learning algorithms. The conventional method achieved similar median performance as the machine learning models but was worse than the best machine learning models and relatively insensitive to predictor choices. Of the machine learning models, decision tree algorithms performed the best in cross-validation experiments, even with a baseline predictor set, and artificial neural networks showed comparable performance when using all predictors. Soil temperature was frequently the most important predictor whilst water table depth was important at sites with substantial water table fluctuations, highlighting the value of data on wetland soil conditions. Raw gap-filling uncertainties from the machine learning models were underestimated and we propose a method to calibrate uncertainties to observations. The python code for model development, evaluation, and uncertainty estimation is publicly available. This study outlines a modular and robust machine learning workflow and makes recommendations for, and evaluates an improved baseline of, methane gap-filling models that can be implemented in multi-site syntheses or standardized products from regional and global flux networks (e.g., FLUXNET)
Non-motor symptom burden in patients with Parkinson's disease with impulse control disorders and compulsive behaviours : results from the COPPADIS cohort
The study was aimed at analysing the frequency of impulse control disorders (ICDs) and compulsive behaviours (CBs) in patients with Parkinson's disease (PD) and in control subjects (CS) as well as the relationship between ICDs/CBs and motor, nonmotor features and dopaminergic treatment in PD patients. Data came from COPPADIS-2015, an observational, descriptive, nationwide (Spain) study. We used the validated Questionnaire for Impulsive-Compulsive Disorders in Parkinson's Disease-Rating Scale (QUIP-RS) for ICD/CB screening. The association between demographic data and ICDs/CBs was analyzed in both groups. In PD, this relationship was evaluated using clinical features and treatment-related data. As result, 613 PD patients (mean age 62.47 ± 9.09 years, 59.87% men) and 179 CS (mean age 60.84 ± 8.33 years, 47.48% men) were included. ICDs and CBs were more frequent in PD (ICDs 12.7% vs. 1.6%, p < 0.001; CBs 7.18% vs. 1.67%, p = 0.01). PD patients had more frequent previous ICDs history, premorbid impulsive personality and antidepressant treatment (p < 0.05) compared with CS. In PD, patients with ICDs/CBs presented younger age at disease onset, more frequent history of previous ICDs and premorbid personality (p < 0.05), as well as higher comorbidity with nonmotor symptoms, including depression and poor quality of life. Treatment with dopamine agonists increased the risk of ICDs/CBs, being dose dependent (p < 0.05). As conclusions, ICDs and CBs were more frequent in patients with PD than in CS. More nonmotor symptoms were present in patients with PD who had ICDs/CBs compared with those without. Dopamine agonists have a prominent effect on ICDs/CBs, which could be influenced by dose
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