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 $\rm W_{H\alpha}$ vs. [NII]/H$\alpha$ (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 $\log$ [OIII]/H$\beta$, $\log$ [NII]/H$\alpha$, and $\log$ EW(H${\alpha}$), 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

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

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 dating’ 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 dating’ 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