25,876 research outputs found
Modelling radiation emission in the transition from the classical to the quantum regime
An emissivity formula is derived using the generalised
Fermi-Weizacker-Williams method of virtual photons which accounts for the
recoil the charged particle experiences as it emits radiation. It is found that
through this derivation the formula obtained by Sokolov et al using QED
perturbation theory is recovered. The corrected emissivity formula is applied
to nonlinear Thomson scattering scenarios in the transition from the classical
to the quantum regime, for small values of the nonlinear quantum parameter
\chi. Good agreement is found between this method and a QED probabilistic
approach for scenarios where both are valid. In addition, signatures of the
quantum corrections are identified and explored.Comment: 11 pages, 4 figures, submitted for publicatio
A probabilistic approach to emission-line galaxy classification
We invoke a Gaussian mixture model (GMM) to jointly analyse two traditional
emission-line classification schemes of galaxy ionization sources: the
Baldwin-Phillips-Terlevich (BPT) and vs. [NII]/H
(WHAN) diagrams, using spectroscopic data from the Sloan Digital Sky Survey
Data Release 7 and SEAGal/STARLIGHT datasets. We apply a GMM to empirically
define classes of galaxies in a three-dimensional space spanned by the
[OIII]/H, [NII]/H, and EW(H), optical
parameters. The best-fit GMM based on several statistical criteria suggests a
solution around four Gaussian components (GCs), which are capable to explain up
to 97 per cent of the data variance. Using elements of information theory, we
compare each GC to their respective astronomical counterpart. GC1 and GC4 are
associated with star-forming galaxies, suggesting the need to define a new
starburst subgroup. GC2 is associated with BPT's Active Galaxy Nuclei (AGN)
class and WHAN's weak AGN class. GC3 is associated with BPT's composite class
and WHAN's strong AGN class. Conversely, there is no statistical evidence --
based on four GCs -- for the existence of a Seyfert/LINER dichotomy in our
sample. Notwithstanding, the inclusion of an additional GC5 unravels it. The
GC5 appears associated to the LINER and Passive galaxies on the BPT and WHAN
diagrams respectively. Subtleties aside, we demonstrate the potential of our
methodology to recover/unravel different objects inside the wilderness of
astronomical datasets, without lacking the ability to convey physically
interpretable results. The probabilistic classifications from the GMM analysis
are publicly available within the COINtoolbox
(https://cointoolbox.github.io/GMM\_Catalogue/).Comment: Accepted for publication in MNRA
HST's view of the youngest massive stars in the Magellanic Clouds
Accurate physical parameters of newborn massive stars are essential
ingredients to shed light on their formation, which is still an unsolved
problem. The rare class of compact H II regions in the Magellanic Clouds (MCs),
termed ``high-excitation blobs'' (HEBs), presents a unique opportunity to
acquire this information. These objects (~ 4" to 10", ~ 1 to 3 pc, in diameter)
harbor the youngest massive stars of the OB association/molecular cloud
complexes in the MCs accessible through high-resolution near-IR and optical
techniques. We present a brief overview of the results obtained with HST mainly
on two HEBs, one in the LMC (N159-5) and the other in the SMC (N81).Comment: 5 pages, to appear in the Proceedings of the 41st ESLAB Symposium
"The Impact of HST on European Astronomy", 29 May to 1 June 2007, ESTEC,
Noordwijk, Netherlands; eds. Guido De Marchi and Duccio Macchett
Colour and chlorophyll's degradation kinetics of frozen green beans (Phaseolus Vulgaris, L.)
Colour changes and chlorophyll's degradation of frozen green beans (Phaseolus vulgaris, L., variety bencanta) were studied during 250 days of storage at -7, -15 and -30°C. Chlorophyll's a and b losses were modelled by a first order reaction kinetics. Colour Hunter a and b coordinates and total colour difference were successfully described by a first order reversible model. The temperature effect was well mathematically described by the Arrhenius law, for both quality parameters
Frozen green beans (Phaseolus vulgaris, L.) quality profile evaluation during home storage
Home storage is at the end of the frozen foods distribution chain, and not much is known how it affects frozen vegetables quality.
This research presents a computational evaluation of frozen green beans (Phaseolus vulgaris, L.) quality profile, in terms of ascorbic
acid, starch content, chlorophylls a and b, colour (Hunter a and b co-ordinates and total colour difference) and flavour, at storage
temperatures of +5, )6, )12 and )18 C, for respectively, 1, 4, 14, and 60 days. Simulations were set to access the impact of the preestablished
after sale dates of the star datingâ system.
Results demonstrate that green beans nutritional and sensory parameters are well retained at the storage temperatures of +5, )6
and )12 C. At )18 C, sensory parameters (e.g. colour and flavour) are well retained, but nutritional parameters, such as ascorbic
acid and starch, degraded. The study concluded that the star datingâ system is a good after sale dating system for frozen green beans
for the storage temperatures of +5, )6 and )12 C. The system fails to maintain a good balance between sensory and nutritional
parameters at low storage temperatures (e.g. <)18 C)
Texture losses of green beans along frozen storage
The texture loss of frozen green beans ( Phaseolus vulgaris, L., variety Bencanta) was
macroscopically evaluated by a puncture test, using the INSTRON (Universal Testing Machine, model 4500) with a 4,85 mm diameter plunger, along 250 days of isothermal storage at -7, -15 and -30°C. The force deformation curves were recorded for data analysis of: i) Energy - the area below the force deformation curve, as a measurement of the resistance to compression by the
plunger, ii) Stress at the failure point - pressure at the failure point, as an index of firmness and iii) Stiffness -Stress / Strain, both at the failure point. The force deformation curves exhibit a decrease in the resistance to compression, with storage
time at all studied temperatures. For longer periods of storage, the well-defined failure point, that is a characteristic of fresh green beans, decreases in Stress magnitude and increases in Strain, corresponding to the softening of green beans initia texture.The softening of the green beans
tissues was assessed by the decrease in Energy, Stress and Stiffness along storage time and at the three studied temperatures. This texture loss has an exponential behaviour, with a residual value of texture that is maintained for a long period of storage. Thus, the softening process was
modelled with a first reversible order kinetics. The kinetic parameters were estimated by nonlinear regression to all data, maximising the likelihood function and solving the normal equations by the Gauss-Newton algorithm. Although the high biological variability observed in the texture of green beans influence the precision of the estimated kinetic parameters, the temperature effec was well described by an Arrhenius behaviour. This research work lead to the conclusion that the softening of frozen stored green beans, is an irreversible degradation of texture, and is an important quality attribute, that can be macroscopically described
Constraining the evolution of the CMB temperature with SZ measurements from Planck data
The CMB temperature-redshift relation, T_CMB(z)=T_0(1+z), is a key prediction
of the standard cosmology, but is violated in many non standard models.
Constraining possible deviations to this law is an effective way to test the
LambdaCDM paradigm and to search for hints of new physics. We have determined
T_CMB(z), with a precision up to 3%, for a subsample (104 clusters) of the
Planck SZ cluster catalog, at redshift in the range 0.01-- 0.94, using
measurements of the spectrum of the Sunyaev Zel'dovich effect obtained from
Planck temperature maps at frequencies from 70 to 353 GHz. The method adopted
to provide individual determinations of T_CMB(z) at cluster redshift relies on
the use of SZ intensity change, Delta I_SZ(nu), at different frequencies, and
on a Monte-Carlo Markov Chain approach. By applying this method to the sample
of 104 clusters, we limit possible deviations of the form
T_CMB(z)=T_0(1+z)^(1-beta) to be beta= 0.022 +/- 0.018, at 1 sigma uncertainty,
consistent with the prediction of the standard model. Combining these
measurements with previously published results we get beta=0.016+/-0.012.Comment: submitted to JCAP, 21 pages, 8 figure
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