Flavonoids: Classification, Biosynthesis and Chemical Ecology

Flavonoids are natural products widely distributed in the plant kingdom and form one of the main classes of secondary metabolites. They display a large range of structures and ecological significance (e.g., such as the colored pigments in many flower petals), serve as chemotaxonomic marker compounds and have a variety of biological activities. Therefore, they have been extensively investigated but the interest in them is still increasing. The topics that will be discussed in this chapter describe the regulation of flavonoid biosynthesis, the roles of flavonoids in flowers, fruits and roots and mechanisms involved in pollination and their specific functions in the plant

Heat Transfer and Fluid Flow Investigations in PDMS Microchannel Heat Sinks Fabricated by Means of a Low-Cost 3D Printer

Polydimethylsiloxane (PDMS), due to its remarkable properties such as optical transparency and ability to easily mold, is one of the most popular polymers used in micro- and nanofluidics. Furthermore, 3D printing technology due to its low cost and simplicity is also gaining a great interest among the microfluidic community. In this work, the potential of 3D printing is shown to produce microfluidic devices, their ability for studying flows and heat transfer of nanofluids, and their applicability as a heat sink device. The low-cost fused deposition modeling 3D printing technique was combined with a PDMS casting technique for the microfluidic device fabrication. The potential of this technique was experimentally demonstrated by fluid flow and heat transfer investigations using different fluids, such as distilled water-, alumina (Al2O3)-, and iron oxide (Fe3O4)-based nanofluids. The simplicity, low-cost, and unique features of the proposed heat sink device may provide a promising way to investigate nanofluids’ flow and heat transfer phenomena that are not possible to be studied by the current traditional systems

Transfer learning for galaxy morphology from one survey to another

© 2018 The Author(s). Published by Oxford University Press on behalf of the Royal Astronomical Society.Deep Learning (DL) algorithms for morphological classification of galaxies have proven very successful, mimicking (or even improving) visual classifications. However, these algorithms rely on large training samples of labelled galaxies (typically thousands of them). A key question for using DL classifications in future Big Data surveys is how much of the knowledge acquired from an existing survey can be exported to a new dataset, i.e. if the features learned by the machines are meaningful for different data. We test the performance of DL models, trained with Sloan Digital Sky Survey (SDSS) data, on Dark Energy survey (DES) using images for a sample of $\sim$5000 galaxies with a similar redshift distribution to SDSS. Applying the models directly to DES data provides a reasonable global accuracy ($\sim$ 90%), but small completeness and purity values. A fast domain adaptation step, consisting in a further training with a small DES sample of galaxies ($\sim$500-300), is enough for obtaining an accuracy > 95% and a significant improvement in the completeness and purity values. This demonstrates that, once trained with a particular dataset, machines can quickly adapt to new instrument characteristics (e.g., PSF, seeing, depth), reducing by almost one order of magnitude the necessary training sample for morphological classification. Redshift evolution effects or significant depth differences are not taken into account in this study.Peer reviewedFinal Accepted Versio

Large-Scale Power Spectrum and Structures From the ENEAR galaxy Peculiar Velocity Catalog

We estimate the mass density fluctuations power spectrum (PS) on large scales by applying a maximum likelihood technique to the peculiarvelocity data of the recently completed redshift-distance survey of early-type galaxies (ENEAR). The general results are in agreement with the high amplitude power spectra found from similar analysis of other independent all-sky catalogs of peculiar velocity data such as MARK III and SFI. For Lambda & Open CDM COBE normalized PS models, the best-fit parameters are confined by a contour approximately defined by Omega h^{1.3}=0.377+-0.08 and Omega h^{0.88}=0.517+-0.083, respectively. Gamma-shape models, free of COBE normalization, resultsin the weak constraint of $\Gamma \geq 0.17$ and in the rather stringent constraint of sigma_8 Omega^{0.6}=1.0+-0.25. All quoted uncertainties refer to 3-sigma confidence-level. The calculated PS is used as a prior for Wiener reconstruction of the density field at different resolutions and the three-dimensional velocity field within a volume of radius ~80 Mpc/h. All major structures in the nearby universe are recovered and are well matched to those predicted from all-sky redshift surveys.Comment: Submitted to MNRAS, 11 Pages, 9 figure

Measurement Of The Σ̄- Lifetime And Direct Comparison With The Σ+ Lifetime

We have measured the lifetime of the Σ̄- using the Fermilab Proton Center 375 GeV/c charged hyperon beam. We obtained (80.43±0.80±0.14) ps. We also measured the lifetime of the Σ+, obtaining (80.38 ±0.40±0.14) ps, in agreement with the Particle Data Group value. A direct comparison between the two lifetimes from the ratio of the decay curves gives a fractional lifetime difference of Δτ/τ=(-0.06±1.12)%, consistent with equal lifetimes for baryon and antibaryon as required by CPT invariance. ©1999 The American Physical Society.61314Foucher, M., (1992) Phys. Rev. Lett., 68, p. 3004Timm, S., (1995) Phys. Rev. D, 51, p. 4638Dubbs, T., (1994) Phys. Rev. Lett., 72, p. 808Caso, C., (1998) Eur. Phys. J. C, 3, p. 690(1993) GEANT 3.21 CERN Program Library W5103, , CERNKuropatkin, N., private communicationLangland, J.L., (1995) Hyperon and Antihyperon Production in P-Cu Interactions, , Ph.D. thesis, University of IowaMorelos, A., (1993) Phys. Rev. Lett., 71, p. 341

DES13S2cmm: the first superluminous supernova from the Dark Energy Survey

We present DES13S2cmm, the first spectroscopically-confirmed superluminous supernova (SLSN) from the Dark Energy Survey (DES). We briefly discuss the data and search algorithm used to find this event in the first year of DES operations, and outline the spectroscopic data obtained from the European Southern Observatory (ESO) Very Large Telescope to confirm its redshift (z = 0.663 +/- 0.001 based on the host-galaxy emission lines) and likely spectral type (type I). Using this redshift, we find M_U_peak = -21.05 +0.10 -0.09 for the peak, rest-frame U-band absolute magnitude, and find DES13S2cmm to be located in a faint, low metallicity (sub-solar), low stellar-mass host galaxy (log(M/M_sun) = 9.3 +/- 0.3); consistent with what is seen for other SLSNe-I. We compare the bolometric light curve of DES13S2cmm to fourteen similarly well-observed SLSNe-I in the literature and find it possesses one of the slowest declining tails (beyond +30 days rest frame past peak), and is the faintest at peak. Moreover, we find the bolometric light curves of all SLSNe-I studied herein possess a dispersion of only 0.2-0.3 magnitudes between +25 and +30 days after peak (rest frame) depending on redshift range studied; this could be important for 'standardising' such supernovae, as is done with the more common type Ia. We fit the bolometric light curve of DES13S2cmm with two competing models for SLSNe-I - the radioactive decay of 56Ni, and a magnetar - and find that while the magnetar is formally a better fit, neither model provides a compelling match to the data. Although we are unable to conclusively differentiate between these two physical models for this particular SLSN-I, further DES observations of more SLSNe-I should break this degeneracy, especially if the light curves of SLSNe-I can be observed beyond 100 days in the rest frame of the supernova.Comment: Accepted by MNRAS (2015 January 23), 13 pages, 6 figures, 2 table

DES15E2mlf: a spectroscopically confirmed superluminous supernova that exploded 3.5 Gyr after the big bang

We present the Dark Energy Survey (DES) discovery of DES15E2mlf, the most distant superluminous supernova (SLSN) spectroscopically confirmed to date. The light curves and Gemini spectroscopy of DES15E2mlf indicate that it is a Type I superluminous supernova (SLSN-I) at z = 1.861 (a lookback time of ∼10 Gyr) and peaking at MAB = −22.3 ± 0.1 mag. Given the high redshift, our data probe the rest-frame ultraviolet (1400–3500 Å) properties of the SN, finding velocity of the C III feature changes by ∼5600 km s−1 over 14 d around maximum light. We find the host galaxy of DES15E2mlf has a stellar mass of 3.5+3.6 −2.4 × 109 M, which is more massive than the typical SLSN-I host galaxy

Superluminous supernovae from the Dark Energy Survey

We present a sample of 21 hydrogen-free superluminous supernovae (SLSNe-I) and one hydrogen-rich SLSN (SLSN-II) detected during the five-year Dark Energy Survey (DES). These SNe, located in the redshift range 0.220 < z < 1.998, represent the largest homogeneously selected sample of SLSN events at high redshift. We present the observed g, r, i, z light curves for these SNe, which we interpolate using Gaussian processes. The resulting light curves are analysed to determine the luminosity function of SLSNe-I, and their evolutionary timescales. The DES SLSN-I sample significantly broadens the distribution of SLSN-I light-curve properties when combined with existing samples from the literature. We fit a magnetar model to our SLSNe, and find that this model alone is unable to replicate the behaviour of many of the bolometric light curves. We search the DES SLSN-I light curves for the presence of initial peaks prior to the main light-curve peak. Using a shock breakout model, our Monte Carlo search finds that 3 of our 14 events with pre-max data display such initial peaks. However, 10 events show no evidence for such peaks, in some cases down to an absolute magnitude of<−16, suggesting that such features are not ubiquitous to all SLSN-I events. We also identify a red pre-peak feature within the light curve of one SLSN, which is comparable to that observed within SN2018bsz

DES science portal: Computing photometric redshifts

A significant challenge facing photometric surveys for cosmological purposes is the need to produce reliable redshift estimates. The estimation of photometric redshifts (photo-zs) has been consolidated as the standard strategy to bypass the high production costs and incompleteness of spectroscopic redshift samples. Training-based photo-z methods require the preparation of a high-quality list of spectroscopic redshifts, which needs to be constantly updated. The photo-z training, validation, and estimation must be performed in a consistent and reproducible way in order to accomplish the scientific requirements. To meet this purpose, we developed an integrated web-based data interface that not only provides the framework to carry out the above steps in a systematic way, enabling the ease testing and comparison of different algorithms, but also addresses the processing requirements by parallelizing the calculation in a transparent way for the user. This framework called the Science Portal (hereafter Portal) was developed in the context the Dark Energy Survey (DES) to facilitate scientific analysis. In this paper, we show how the Portal can provide a reliable environment to access vast datasets, provide validation algorithms and metrics, even in the case of multiple photo-zs methods. It is possible to maintain the provenance between the steps of a chain of workflows while ensuring reproducibility of the results. We illustrate how the Portal can be used to provide photo-z estimates using the DES first year (Y1A1) data. While the DES collaboration is still developing techniques to obtain more precise photo-zs, having a structured framework like the one presented here is critical for the systematic vetting of DES algorithmic improvements and the consistent production of photo-zs in future DES releases