6,744 research outputs found

    Prognostic value of CA125 in advanced heart failure patients

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    INTRODUCTION: Serum levels of CA125 are often high in advanced heart failure (AHF) patients. AIM: To determine the predictive value of CA125 in forecasting the occurrence of death or cardiac transplantation in an AHF population. METHODS: 88 AHF patients referred for heart transplantation were divided into 2 groups based on CA125 levels: normal (CA125/=38 U/mL). Events (death or heart transplant) were monitored over a period of 13+/-7 months after CA125 determination. RESULTS: Patients with elevated CA125 (n=65) had significantly lower blood pressure, body mass index, serum sodium and peak exercise oxygen consumption, while B-type natriuretic peptide levels were significantly higher. The combined primary endpoint (death or heart transplant) rate was 39.4% and 62.3% in normal and elevated CA125 groups, respectively (p=0.029). Multivariate regression analysis showed that CA125 and sodium levels were the only independent predictors of the combined endpoint. CONCLUSION: In AHF patients, plasma CA125 was an effective prognostic marker. Its determination may contribute to better risk stratification in this population

    Predicting Psi-BN: computational insights into its mechanical, electronic, and optical characteristics

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    Computational materials are pivotal in advancing our understanding of distinct material classes and their properties, offering valuable insights in predicting novel structures and complementing experimental approaches. In this context, Psi-graphene is a stable two-dimensional carbon allotrope composed of 5-6-7 carbon rings theoretically predicted recently. Using density functional theory (DFT) calculations, we explored its boron nitride counterpart's mechanical, electronic, and optical characteristics (Psi-BN). Our results indicate that Psi-BN possesses a band gap of 4.59 eV at the HSE06 level. Phonon calculations and ab initio molecular dynamics simulations demonstrated that this material has excellent structural and dynamic stability. Moreover, its formation energy is -7.48 eV. Psi-BN exhibited strong ultraviolet activity, suggesting its potential as an efficient UV collector. Furthermore, we determined critical mechanical properties of Psi-BN, such as the elastic stiffness constants, Young's modulus (250-300 GPa), and Poisson ratio (0.7), providing valuable insights into its mechanical behavior.Comment: 13 pages, 7 figure

    The role of front-end ac/dc converters in hybrid ac/dc smart homes: Analysis and experimental validation

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    Electrical power grids are rapidly evolving into smart grids, with smart homes also making an important contribution to this. In fact, the well-known and emerging technologies of renewables, energy storage systems and electric mobility are each time more distributed throughout the power grid and included in smart homes. In such circumstances, since these technologies are natively operating in DC, it is predictable for a revolution in the electrical grid craving a convergence to DC grids. Nevertheless, traditional loads natively operating in AC will continue to be used, highlighting the importance of hybrid AC/DC grids. Considering this new paradigm, this paper has as main innovation points the proposed control algorithms regarding the role of front-end AC/DC converters in hybrid AC/DC smart homes, demonstrating their importance for providing unipolar or bipolar DC grids for interfacing native DC technologies, such as renewables and electric mobility, including concerns regarding the power quality from a smart grid point of view. Furthermore, the paper presents a clear description of the proposed control algorithms, aligned with distinct possibilities of complementary operation of front-end AC/DC converters in the perspective of smart homes framed within smart grids, e.g., enabling the control of smart homes in a coordinated way. The analysis and experimental results confirmed the suitability of the proposed innovative operation modes for hybrid AC/DC smart homes, based on two different AC/DC converters in the experimental validation

    A large sample of calibration stars for Gaia: log g from Kepler and CoRoT

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    Asteroseismic data can be used to determine surface gravities with precisions of < 0.05 dex by using the global seismic quantities Deltanu and nu_max along with Teff and [Fe/H]. Surface gravity is also one of the four stellar properties to be derived by automatic analyses for 1 billion stars from Gaia data (workpackage GSP_Phot). We explore seismic data from MS F, G, K stars (solar-like stars) observed by Kepler as a potential calibration source for methods that Gaia will use for object characterisation (log g). We calculate log g for bright nearby stars for which radii and masses are known, and using their global seismic quantities in a grid-based method, we determine an asteroseismic log g to within 0.01 dex of the direct calculation, thus validating the accuracy of our method. We find that errors in Teff and mainly [Fe/H] can cause systematic errors of 0.02 dex. We then apply our method to a list of 40 stars to deliver precise values of surface gravity, i.e. sigma < 0.02 dex, and we find agreement with recent literature values. Finally, we explore the precision we expect in a sample of 400+ Kepler stars which have their global seismic quantities measured. We find a mean uncertainty (precision) on the order of <0.02 dex in log g over the full explored range 3.8 < log g < 4.6, with the mean value varying only with stellar magnitude (0.01 - 0.02 dex). We study sources of systematic errors in log g and find possible biases on the order of 0.04 dex, independent of log g and magnitude, which accounts for errors in the Teff and [Fe/H] measurements, as well as from using a different grid-based method. We conclude that Kepler stars provide a wealth of reliable information that can help to calibrate methods that Gaia will use, in particular, for source characterisation with GSP_Phot where excellent precision (small uncertainties) and accuracy in log g is obtained from seismic data.Comment: Accepted MNRAS, 15 pages (10 figures and 3 tables), v2=some rewording of two sentence
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