A search of neutral gas outflows in nearby luminous star-forming galaxies

Tesis doctoral inédita leída en la Universidad Autónoma de Madrid, Facultad de Ciencias, Departamento de Física Teórica. Fecha de lectura: 27-05-2016This thesis was funded by the Marie Curie Initial Training Network ELIXIR (PI: Stéphane Charlot) of the European Commission under contract PITN- GA-2008-214227 and the grants AYA2010-21161-C02-01 and AYA2012-32295 by the Spanish Ministry of Science and Innovation (MICINN). S.C. gratefully acknowledges the logistic and financial support provided by the Cavendish Laboratory (Cambridge, UK

Star-formation histories of local luminous infrared galaxies

We present the analysis of the integrated spectral energy distribution (SED) from the ultraviolet (UV) to the far-infrared and H$\alpha$ of a sample of 29 local systems and individual galaxies with infrared (IR) luminosities between 10^11 Lsun and 10^11.8 Lsun. We have combined new narrow-band H$\alpha$+[NII] and broad-band g, r optical imaging taken with the Nordic Optical Telescope (NOT), with archival GALEX, 2MASS, Spitzer, and Herschel data. The SEDs (photometry and integrated H$\alpha$ flux) have been fitted with a modified version of the MAGPHYS code using stellar population synthesis models for the UV-near-IR range and thermal emission models for the IR emission taking into account the energy balance between the absorbed and re-emitted radiation. From the SED fits we derive the star-formation histories (SFH) of these galaxies. For nearly half of them the star-formation rate appears to be approximately constant during the last few Gyrs. In the other half, the current star-formation rate seems to be enhanced by a factor of 3-20 with respect to that occured ~1 Gyr ago. Objects with constant SFH tend to be more massive than starbursts and they are compatible with the expected properties of a main-sequence (M-S) galaxy. Likewise, the derived SFHs show that all our objects were M-S galaxies ~1 Gyr ago with stellar masses between 10^10.1 and 10^11.5 Msun. We also derived from our fits the average extinction (A_v=0.6-3 mag) and the polycyclic aromatic hydrocarbons (PAH) luminosity to L(IR) ratio (0.03-0.16). We combined the A_v with the total IR and H$\alpha$ luminosities into a diagram which can be used to identify objects with rapidly changing (increasing or decreasing) SFR during the last 100 Myr.Comment: 16 pages + online material, accepted for publication in A&

Surface-based integration approach for fNIRS-fMRI reliability assessment

Introduction: Studies integrating functional near-infrared spectroscopy (fNIRS) with functional MRI (fMRI) employ heterogeneous methods in defining common regions of interest in which similarities are assessed. Therefore, spatial agreement and temporal correlation may not be reproducible across studies. In the present work, we address this issue by proposing a novel method for integration and analysis of fNIRS and fMRI over the cortical surface. Materials and methods: Eighteen healthy volunteers (age mean±SD 30.55 ± 4.7, 7 males) performed a motor task during non-simultaneous fMRI and fNIRS acquisitions. First, fNIRS and fMRI data were integrated by projecting subject- and group-level source maps over the cortical surface mesh to define anatomically constrained functional ROIs (acfROI). Next, spatial agreement and temporal correlation were quantified as Dice Coefficient (DC) and Pearson's correlation coefficient between fNIRS-fMRI in the acfROIs. Results: Subject-level results revealed moderate to substantial spatial agreement (DC range 0.43 - 0.64), confirmed at the group-level only for blood oxygenation level-dependent (BOLD) signal vs. HbO2 (0.44 - 0.69), while lack of agreement was found for BOLD vs. HbR in some instances (0.05 - 0.49). Subject-level temporal correlation was moderate to strong (0.79 - 0.85 for BOLD vs. HbO2 and -0.62 to -0.72 for BOLD vs. HbR), while an overall strong correlation was found for group-level results (0.95 - 0.98 for BOLD vs. HbO2 and -0.91 to -0.94 for BOLD vs. HbR). Conclusion: The proposed method directly compares fNIRS and fMRI by projecting individual source maps to the cortical surface. Our results indicate spatial and temporal correspondence between fNIRS and fMRI, and promotes the use of fNIRS when more ecological acquision settings are required, such as longitudinal monitoring of brain activity before and after rehabilitation

The AGN nature of LINER nuclear sources

Properties of LINERs

The [OIII] profiles of far-infrared active and non-active optically-selected green valley galaxies

We present a study of the $\rm{[OIII]\lambda\,5007}$ line profile in a sub-sample of 8 active galactic nuclei (AGN) and 6 non-AGN in the optically-selected green valley at $\rm{z\,<\,0.5}$ using long-slit spectroscopic observations with the 11 m Southern African Large Telescope. Gaussian decomposition of the line profile was performed to study its different components. We observe that the AGN profile is more complex than the non-AGN one. In particular, in most AGN (5/8) we detect a blue wing of the line. We derive the FWHM velocities of the wing and systemic component, and find that AGN show higher FWHM velocity than non-AGN in their core component. We also find that the AGN show blue wings with a median velocity width of approximately 600 $\rm{km\,s^{-1}}$, and a velocity offset from the core component in the range -90 to -350 $\rm{km\,s^{-1}}$, in contrast to the non-AGN galaxies, where we do not detect blue wings in any of their $\rm{[OIII]\lambda\,5007}$ line profiles. Using spatial information in our spectra, we show that at least three of the outflow candidate galaxies have centrally driven gas outflows extending across the whole galaxy. Moreover, these are also the galaxies which are located on the main sequence of star formation, raising the possibility that the AGN in our sample are influencing SF of their host galaxies (such as positive feedback). This is in agreement with our previous work where we studied SF, morphology, and stellar population properties of a sample of green valley AGN and non-AGN galaxies.Comment: 15 pages, 6 figures, accepted for publication in Ap

NEUROPHYSIOLOGICAL SIGNIFICANCE OF "GIANT" SOMATOSENSORY POTENTIALS IN MOTONEURON PATHOLOGY

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Negative and Positive Outflow-Feedback in Nearby (U)LIRGs

The starburst-AGN coexistence in local (U)LIRGs makes these galaxies excellent laboratories for the study of stellar and AGN outflows and feedback. Outflows regulate star formation and AGN activity, redistributing gas, dust and metals over large scales in the interstellar and intergalactic media (negative feedback) being also considered to be able to undergo vigorous star formation (positive feedback). In this contribution, I will summarize the results from a search for outflows in a sample of nearby 38 local (U)LIRG systems observed with VIMOS/VLT integral field unit. For two galaxies of the sample I will detail the outflow properties and discuss the observational evidence for negative and positive outflow-feedback. The assessment of both negative and positive feedback effects represent a novel approach toward a comprehensive understanding of the impact of outflow feedback in the galaxy evolution

Negative and positive outflow-feedback in nearby (U)LIRGs

<p>AGN Feedback can reconcile theory and observations</p

Negative and positive outflow-feedback in nearby (U)LIRGs

<p>The starburst-AGN coexistence in local (U)LIRGs makes these galaxies excellent laboratories for the study of stellar and AGN outflows and feedback. Outflows regulate star formation and AGN activity, redistributing gas, dust and metals over large scales in the interstellar and intergalactic media (negative feedback) being also considered to be able to undergo vigorous star formation (positive feedback). In this contribution, I will present results from a search for outflows in a sample of 38 local (U)LIRG systems (Cazzoli et al. 2016) observed with VIMOS/VLT integral field unit. Then, for two galaxies of the sample I will detail the outflow properties and discuss the observational evidence for negative and positive outflow-feedback.</p