20 research outputs found
Reddening-free Q indices to identify Be star candidates
Astronomical databases currently provide high-volume spectroscopic and
photometric data. While spectroscopic data is better suited to the analysis of
many astronomical objects, photometric data is relatively easier to obtain due
to shorter telescope usage time. Therefore, there is a growing need to use
photometric information to automatically identify objects for further detailed
studies, specially H{\alpha} emission line stars such as Be stars. Photometric
color-color diagrams (CCDs) are commonly used to identify this kind of objects.
However, their identification in CCDs is further complicated by the reddening
effect caused by both the circumstellar and interstellar gas. This effect
prevents the generalization of candidate identification systems. Therefore, in
this work we evaluate the use of neural networks to identify Be star candidates
from a set of OB-type stars. The networks are trained using a labeled subset of
the VPHAS+ and 2MASS databases, with filters u, g, r, H{\alpha}, i, J, H, and
K. In order to avoid the reddening effect, we propose and evaluate the use of
reddening-free Q indices to enhance the generalization of the model to other
databases and objects. To test the validity of the approach, we manually
labeled a subset of the database, and use it to evaluate candidate
identification models. We also labeled an independent dataset for cross dataset
evaluation. We evaluate the recall of the models at a 99% precision level on
both test sets. Our results show that the proposed features provide a
significant improvement over the original filter magnitudes.Comment: 14 pages, 4 figures, Accepted for inclusion in the JCC-BD&ET 2020
minutes book, which will be published in the Springer series CCIS -
Communications in Computer and Information Scienc
Disease-Toxicant Interactions in Manganese Exposed Huntington Disease Mice: Early Changes in Striatal Neuron Morphology and Dopamine Metabolism
YAC128 Huntington's disease (HD) transgenic mice accumulate less manganese (Mn) in the striatum relative to wild-type (WT) littermates. We hypothesized that Mn and mutant Huntingtin (HTT) would exhibit gene-environment interactions at the level of neurochemistry and neuronal morphology. Twelve-week-old WT and YAC128 mice were exposed to MnCl2-4H2O (50 mg/kg) on days 0, 3 and 6. Striatal medium spiny neuron (MSN) morphology, as well as levels of dopamine (DA) and its metabolites (which are known to be sensitive to Mn-exposure), were analyzed at 13 weeks (7 days from initial exposure) and 16 weeks (28 days from initial exposure). No genotype-dependent differences in MSN morphology were apparent at 13 weeks. But at 16 weeks, a genotype effect was observed in YAC128 mice, manifested by an absence of the wild-type age-dependent increase in dendritic length and branching complexity. In addition, genotype-exposure interaction effects were observed for dendritic complexity measures as a function of distance from the soma, where only YAC128 mice were sensitive to Mn exposure. Furthermore, striatal DA levels were unaltered at 13 weeks by genotype or Mn exposure, but at 16 weeks, both Mn exposure and the HD genotype were associated with quantitatively similar reductions in DA and its metabolites. Interestingly, Mn exposure of YAC128 mice did not further decrease DA or its metabolites versus YAC128 vehicle exposed or Mn exposed WT mice. Taken together, these results demonstrate Mn-HD disease-toxicant interactions at the onset of striatal dendritic neuropathology in YAC128 mice. Our results identify the earliest pathological change in striatum of YAC128 mice as being between 13 to 16 weeks. Finally, we show that mutant HTT suppresses some Mn-dependent changes, such as decreased DA levels, while it exacerbates others, such as dendritic pathology
Transport across the vacuolar membrane in CAM plants
Close metabolic parallels exist between the processes of CO2 assimilation in C4 plants and in CAM plants. In both types of plant, a C4 cycle starts with the fixation of CO2 (as HCO3 −) by phosphoenolpyruvate carboxylase (PEPC) and concludes with the release or CO2 by decarboxylation of a C4 dicarboxylate anion (malate or aspartate). This C4 cycle is an ancillary pathway, in the sense that it does not mediate the net fixation of atmospheric CO2. It simply passes on this CO2, at greatly elevated concentration, to ribulose 1,5-bisphosphate carboxylase/oxygenase (RUBISCO) for assimilation through the standard C3 photosynthetic carbon reduction cycle