Spanish National Research Council

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.

The preparation of magnetic nanoparticles for applications in biomedicine

Abstract: This review is focused on describing state-of-the-art synthetic routes for the preparation of magnetic nanoparticles useful for biomedical applications. In addition to this topic, we have also described in some detail some of the possible applications of magnetic nanoparticles in the field of biomedicine with special emphasis on showing the benefits of using nanoparticles. Finally, we have addressed some relevant findings on the importance of having well-defined synthetic routes to produce materials not only with similar physical features but also with similar crystallochemical characteristics.

Carbon capture and storage update

Abstract: In recent years, Carbon Capture and Storage (Sequestration) (CCS) has been proposed as a potential method to allow the continued use of fossil-fuelled power stations whilst preventing emissions of CO2 from reaching the atmosphere. Gas, coal (and biomass)-fired power stations can respond to changes in demand more readily than many other sources of electricity production, hence the importance of retaining them as an option in the energy mix. Here, we review the leading CO2 capture technologies, available in the short and long term, and their technological maturity, before discussing CO2 transport and storage. Current pilot plants and demonstrations are highlighted, as is the importance of optimising the CCS system as a whole. Other topics briefly discussed include the viability of both the capture of CO2 from the air and CO2 reutilisation as climate change mitigation strategies. Finally, we discuss the economic and legal aspects of CCS.

Planck 2018 results: XI. Polarized dust foregrounds

Abstract: The study of polarized dust emission has become entwined with the analysis of the cosmic microwave background (CMB) polarization. We use new Planck maps to characterize Galactic dust emission as a foreground to the CMB polarization. We present Planck EE, BB, and TE power spectra of dust polarization at 353 GHz for six nested sky regions covering from 24 to 71 % of the sky. We present power-law fits to the angular power spectra, yielding evidence for statistically significant variations of the exponents over sky regions and a difference between the values for the EE and BB spectra. The TE correlation and E/B power asymmetry extend to low multipoles that were not included in earlier Planck polarization papers. We also report evidence for a positive TB dust signal. Combining data from Planck and WMAP, we determine the amplitudes and spectral energy distributions (SEDs) of polarized foregrounds, including the correlation between dust and synchrotron polarized emission, for the six sky regions as a function of multipole. This quantifies the challenge of the component separation procedure required for detecting the reionization and recombination peaks of primordial CMB B modes. The SED of polarized dust emission is fit well by a single-temperature modified blackbody emission law from 353 GHz to below 70 GHz. For a dust temperature of 19.6 K, the mean spectral index for dust polarization is $\beta_{\rm d}^{P} = 1.53\pm0.02 $. By fitting multi-frequency cross-spectra, we examine the correlation of the dust polarization maps across frequency. We find no evidence for decorrelation. If the Planck limit for the largest sky region applies to the smaller sky regions observed by sub-orbital experiments, then decorrelation might not be a problem for CMB experiments aiming at a primordial B-mode detection limit on the tensor-to-scalar ratio $r\simeq0.01$ at the recombination peak.

The three-dimensional power spectrum of galaxies from the sloan digital sky survey

Abstract: We measure the large-scale real-space power spectrum P(k) by using a sample of 205,443 galaxies from the Sloan Digital Sky Survey, covering 2417 effective square degrees with mean redshift z ≈ 0.1. We employ a matrix-based method using pseudo-Karhunen-Loeve eigenmodes, producing uncorrelated minimum-variance measurements in 22 k-bands of both the clustering power and its anisotropy due to redshift-space distortions, with narrow and well-behaved window functions in the range 0.02 h Mpc-1 < k < 0.3 h Mpc-1. We pay particular attention to modeling, quantifying, and correcting for potential systematic errors, nonlinear redshift distortions, and the artificial red-tilt caused by luminosity-dependent bias. Our results are robust to omitting angular and radial density fluctuations and are consistent between different parts of the sky. Our final result is a measurement of the real-space matter power spectrum P(k) up to an unknown overall multiplicative bias factor. Our calculations suggest that this bias factor is independent of scale to better than a few percent for k < 0.1 h Mpc-1, thereby making our results useful for precision measurements of cosmological parameters in conjunction with data from other experiments such as the Wilkinson Microwave Anisotropy Probe satellite. The power spectrum is not well-characterized by a single power law but unambiguously shows curvature. As a simple characterization of the data, our measurements are well fitted by a flat scale-invariant adiabatic cosmological model with h Ωm = 0.213 ± 0.023 and σ8 = 0.89 ± 0.02 for L* galaxies, when fixing the baryon fraction Ωb/Ωm = 0.17 and the Hubble parameter h = 0.72; cosmological interpretation is given in a companion paper.

Using network analysis to explore co-occurrence patterns in soil microbial communities

Abstract: Exploring large environmental datasets generated by high-throughput DNA sequencing technologies requires new analytical approaches to move beyond the basic inventory descriptions of the composition and diversity of natural microbial communities. In order to investigate potential interactions between microbial taxa, network analysis of significant taxon co-occurrence patterns may help to decipher the structure of complex microbial communities across spatial or temporal gradients. Here, we calculated associations between microbial taxa and applied network analysis approaches to a 16S rRNA gene barcoded pyrosequencing dataset containing >160 000 bacterial and archaeal sequences from 151 soil samples from a broad range of ecosystem types. We described the topology of the resulting network and defined operational taxonomic unit categories based on abundance and occupancy (that is, habitat generalists and habitat specialists). Co-occurrence patterns were readily revealed, including general non-random association, common life history strategies at broad taxonomic levels and unexpected relationships between community members. Overall, we demonstrated the potential of exploring inter-taxa correlations to gain a more integrated understanding of microbial community structure and the ecological rules guiding community assembly.