14,072 research outputs found
Heterotrophy as a tool to overcome the long and costly autotrophic scale-up process for large scale production of microalgae
Industrial scale-up of microalgal cultures is often a protracted step prone to culture collapse and the occurrence of unwanted contaminants. To solve this problem, a two-stage scale-up process was developed - heterotrophically Chlorella vulgaris cells grown in fermenters (1st stage) were used to directly inoculate an outdoor industrial autotrophic microalgal production unit (2nd stage). A preliminary pilot-scale trial revealed that C. vulgaris cells grown heterotrophically adapted readily to outdoor autotrophic growth conditions (1-m3 photobioreactors) without any measurable difference as compared to conventional autotrophic inocula. Biomass concentration of 174.5 g L-1, the highest value ever reported for this microalga, was achieved in a 5-L fermenter during scale-up using the heterotrophic route. Inocula grown in 0.2- and 5-m3 industrial fermenters with mean productivity of 27.54 ± 5.07 and 31.86 ± 2.87 g L-1 d-1, respectively, were later used to seed several outdoor 100-m3 tubular photobioreactors. Overall, all photobioreactor cultures seeded from the heterotrophic route reached standard protein and chlorophyll contents of 52.18 ± 1.30% of DW and 23.98 ± 1.57 mg g-1 DW, respectively. In addition to providing reproducible, high-quality inocula, this two-stage approach led to a 5-fold and 12-fold decrease in scale-up time and occupancy area used for industrial scale-up, respectively.Agência financiadora
project FERMALG
017608
Fundacao para a Ciencia e a Tecnologia (FCT)
UID/Multi/04326/2019
project FERMALG (AVISO)
32/SI/2015info:eu-repo/semantics/publishedVersio
Optical Surface Photometry of a Sample of Disk Galaxies. II Structural Components
This work presents the structural decomposition of a sample of 11 disk
galaxies, which span a range of different morphological types. The U, B, V, R,
and I photometric information given in Paper I (color and color-index images
and luminosity, ellipticity, and position-angle profiles) has been used to
decide what types of components form the galaxies before carrying out the
decomposition. We find and model such components as bulges, disks, bars, lenses
and rings.Comment: 14 figures. Accepted for publication in A&
Machine learning techniques to select Be star candidates. An application in the OGLE-IV Gaia south ecliptic pole field
Statistical pattern recognition methods have provided competitive solutions
for variable star classification at a relatively low computational cost. In
order to perform supervised classification, a set of features is proposed and
used to train an automatic classification system. Quantities related to the
magnitude density of the light curves and their Fourier coefficients have been
chosen as features in previous studies. However, some of these features are not
robust to the presence of outliers and the calculation of Fourier coefficients
is computationally expensive for large data sets. We propose and evaluate the
performance of a new robust set of features using supervised classifiers in
order to look for new Be star candidates in the OGLE-IV Gaia south ecliptic
pole field. We calculated the proposed set of features on six types of variable
stars and on a set of Be star candidates reported in the literature. We
evaluated the performance of these features using classification trees and
random forests along with K-nearest neighbours, support vector machines, and
gradient boosted trees methods. We tuned the classifiers with a 10-fold
cross-validation and grid search. We validated the performance of the best
classifier on a set of OGLE-IV light curves and applied this to find new Be
star candidates. The random forest classifier outperformed the others. By using
the random forest classifier and colour criteria we found 50 Be star candidates
in the direction of the Gaia south ecliptic pole field, four of which have
infrared colours consistent with Herbig Ae/Be stars. Supervised methods are
very useful in order to obtain preliminary samples of variable stars extracted
from large databases. As usual, the stars classified as Be stars candidates
must be checked for the colours and spectroscopic characteristics expected for
them
Emission Line Galaxies and Active Galactic Nuclei in WINGS clusters
We present the analysis of the emission line galaxies members of 46 low
redshift (0.04 < z < 0.07) clusters observed by WINGS (WIde-field Nearby Galaxy
cluster Survey, Fasano et al. 2006). Emission line galaxies were identified
following criteria that are meant to minimize biases against non-star forming
galaxies and classified employing diagnostic diagrams. We have examined the
emission line properties and frequencies of star forming galaxies, transition
objects and active galactic nuclei (AGNs: LINERs and Seyferts), unclassified
galaxies with emission lines, and quiescent galaxies with no detectable line
emission. A deficit of emission line galaxies in the cluster environment is
indicated by both a lower frequency with respect to control samples, and by a
systematically lower Balmer emission line equivalent width and luminosity (up
to one order of magnitude in equivalent width with respect to control samples
for transition objects) that implies a lower amount of ionised gas per unit
mass and a lower star formation rate if the source is classified as Hii region.
A sizable population of transition objects and of low-luminosity LINERs
(approx. 10 - 20% of all emission line galaxies) is detected among WINGS
cluster galaxies. With respect to Hii sources they are a factor of approx. 1.5
more frequent than (or at least as frequent as) in control samples. Transition
objects and LINERs in cluster are most affected in terms of line equivalent
width by the environment and appear predominantly consistent with "retired"
galaxies. Shock heating can be a possible gas excitation mechanism able to
account for observed line ratios. Specific to the cluster environment, we
suggest interaction between atomic and molecular gas and the intracluster
medium as a possible physical cause of line-emitting shocks.Comment: Astronomy and Astrophysics, accepte
Study of Plants Growth by Image Analysis
Analysis of plants growth is an important step for the evaluation of plants performance and productivity. This paper presents study of plants growth by image analysis from seeds and up to photosynthesis. To extract parameters two different segmentation methods are used, one for the seeds, and one for the plants, combined with morphological operations. The first image segmentation is achieved with Fuzzy C-Means clustering method and the second is achieved with entropy based method, using histogram evaluation. In tests, the segmented image is transformed in binary image and the relevant regions are extracted after applying morphological operation.
The following parameters are calculated: the projected surface, the contour’s perimeter, the seed’s mass center, the projected surface, and the cotyledon’s and hyper cotyledon’slength for the plants
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