Institution
Spanish National Research Council
Government•Madrid, Spain•
About: Spanish National Research Council is a government organization based out in Madrid, Spain. It is known for research contribution in the topics: Population & Galaxy. The organization has 79563 authors who have published 220470 publications receiving 7698991 citations. The organization is also known as: CSIC & Consejo Superior de Investigaciones Científicas.
Topics: Population, Galaxy, Catalysis, Stars, Gene
Papers published on a yearly basis
Papers
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TL;DR: In this paper, the cosmological parameter results from the final full-mission Planck measurements of the CMB anisotropies were presented, with good consistency with the standard spatially-flat 6-parameter CDM cosmology having a power-law spectrum of adiabatic scalar perturbations from polarization, temperature, and lensing separately and in combination.
Abstract: We present cosmological parameter results from the final full-mission Planck measurements of the CMB anisotropies. We find good consistency with the standard spatially-flat 6-parameter $\Lambda$CDM cosmology having a power-law spectrum of adiabatic scalar perturbations (denoted "base $\Lambda$CDM" in this paper), from polarization, temperature, and lensing, separately and in combination. A combined analysis gives dark matter density $\Omega_c h^2 = 0.120\pm 0.001$, baryon density $\Omega_b h^2 = 0.0224\pm 0.0001$, scalar spectral index $n_s = 0.965\pm 0.004$, and optical depth $\tau = 0.054\pm 0.007$ (in this abstract we quote $68\,\%$ confidence regions on measured parameters and $95\,\%$ on upper limits). The angular acoustic scale is measured to $0.03\,\%$ precision, with $100\theta_*=1.0411\pm 0.0003$. These results are only weakly dependent on the cosmological model and remain stable, with somewhat increased errors, in many commonly considered extensions. Assuming the base-$\Lambda$CDM cosmology, the inferred late-Universe parameters are: Hubble constant $H_0 = (67.4\pm 0.5)$km/s/Mpc; matter density parameter $\Omega_m = 0.315\pm 0.007$; and matter fluctuation amplitude $\sigma_8 = 0.811\pm 0.006$. We find no compelling evidence for extensions to the base-$\Lambda$CDM model. Combining with BAO we constrain the effective extra relativistic degrees of freedom to be $N_{\rm eff} = 2.99\pm 0.17$, and the neutrino mass is tightly constrained to $\sum m_
u< 0.12$eV. The CMB spectra continue to prefer higher lensing amplitudes than predicted in base -$\Lambda$CDM at over $2\,\sigma$, which pulls some parameters that affect the lensing amplitude away from the base-$\Lambda$CDM model; however, this is not supported by the lensing reconstruction or (in models that also change the background geometry) BAO data. (Abridged)
3,077 citations
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TL;DR: In all cases, enzyme engineering via immobilization techniques is perfectly compatible with other chemical or biological approaches to improve enzyme functions and the final success depend on the availability of a wide battery of immobilization protocols.
3,016 citations
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TL;DR: The identification of Snail, ZEB and some basic helix-loop-helix factors as inducers of epithelial–mesenchymal transition (EMT) and potent repressors of E-cadherin expression has opened new avenues of research with potential clinical implications.
Abstract: The molecular mechanisms that underlie tumour progression are still poorly understood, but recently our knowledge of particular aspects of some of these processes has increased. Specifically, the identification of Snail, ZEB and some basic helix-loop-helix (bHLH) factors as inducers of epithelial-mesenchymal transition (EMT) and potent repressors of E-cadherin expression has opened new avenues of research with potential clinical implications.
2,975 citations
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TL;DR: This work performs a broad experimental evaluation involving ten methods, three of them proposed by the authors, to deal with the class imbalance problem in thirteen UCI data sets, and shows that, in general, over-sampling methods provide more accurate results than under-sampled methods considering the area under the ROC curve (AUC).
Abstract: There are several aspects that might influence the performance achieved by existing learning systems. It has been reported that one of these aspects is related to class imbalance in which examples in training data belonging to one class heavily outnumber the examples in the other class. In this situation, which is found in real world data describing an infrequent but important event, the learning system may have difficulties to learn the concept related to the minority class. In this work we perform a broad experimental evaluation involving ten methods, three of them proposed by the authors, to deal with the class imbalance problem in thirteen UCI data sets. Our experiments provide evidence that class imbalance does not systematically hinder the performance of learning systems. In fact, the problem seems to be related to learning with too few minority class examples in the presence of other complicating factors, such as class overlapping. Two of our proposed methods deal with these conditions directly, allying a known over-sampling method with data cleaning methods in order to produce better-defined class clusters. Our comparative experiments show that, in general, over-sampling methods provide more accurate results than under-sampling methods considering the area under the ROC curve (AUC). This result seems to contradict results previously published in the literature. Two of our proposed methods, Smote + Tomek and Smote + ENN, presented very good results for data sets with a small number of positive examples. Moreover, Random over-sampling, a very simple over-sampling method, is very competitive to more complex over-sampling methods. Since the over-sampling methods provided very good performance results, we also measured the syntactic complexity of the decision trees induced from over-sampled data. Our results show that these trees are usually more complex then the ones induced from original data. Random over-sampling usually produced the smallest increase in the mean number of induced rules and Smote + ENN the smallest increase in the mean number of conditions per rule, when compared among the investigated over-sampling methods.
2,914 citations
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TL;DR: The Virgo Consortium's EAGLE project as discussed by the authors is a suite of hydrodynamical simulations that follow the formation of galaxies and black holes in representative volumes, where thermal energy is injected into the gas, allowing winds to develop without predetermined speed or mass loading factors.
Abstract: We introduce the Virgo Consortium's EAGLE project, a suite of hydrodynamical simulations that follow the formation of galaxies and black holes in representative volumes. We discuss the limitations of such simulations in light of their finite resolution and poorly constrained subgrid physics, and how these affect their predictive power. One major improvement is our treatment of feedback from massive stars and AGN in which thermal energy is injected into the gas without the need to turn off cooling or hydrodynamical forces, allowing winds to develop without predetermined speed or mass loading factors. Because the feedback efficiencies cannot be predicted from first principles, we calibrate them to the z~0 galaxy stellar mass function and the amplitude of the galaxy-central black hole mass relation, also taking galaxy sizes into account. The observed galaxy mass function is reproduced to ≲0.2 dex over the full mass range, 108
2,828 citations
Authors
Showing all 79686 results
Name | H-index | Papers | Citations |
---|---|---|---|
Guido Kroemer | 236 | 1404 | 246571 |
George Efstathiou | 187 | 637 | 156228 |
Peidong Yang | 183 | 562 | 144351 |
H. S. Chen | 179 | 2401 | 178529 |
David R. Williams | 178 | 2034 | 138789 |
Andrea Bocci | 172 | 2402 | 176461 |
Adrian L. Harris | 170 | 1084 | 120365 |
Gang Chen | 167 | 3372 | 149819 |
Gregory J. Hannon | 165 | 421 | 140456 |
Alvaro Pascual-Leone | 165 | 969 | 98251 |
Jorge E. Cortes | 163 | 2784 | 124154 |
Dongyuan Zhao | 160 | 872 | 106451 |
John B. Goodenough | 151 | 1064 | 113741 |
David D'Enterria | 150 | 1592 | 116210 |
A. Gomes | 150 | 1862 | 113951 |