Modelling the kinetics of thermal inactivation of apple polyphenoloxidase

The enzymatic browning of fruits and vegetables caused by mechanical injury during postharvest storage or processing is initiated by the catalytic action of polyphenoloxidase (PPO). A bleaching treatment prior to processing is still considered mostly effective in inhibiting the catalytic activity of PPO, and thus controlling undesirable enzymatic browning. In this work, different mathematical routines were assessed in terms of their adequacy to describe the thermal inactivation of PPO from Golden apples over a range of temperatures from 62.5 to 72.5 ºC. The classical approach to kinetic modelling of the decay activity of apple PPO, commonly reported to follow a first-order model, employs a two-step procedure, in which the model parameters are individually obtained, by each temperature studied, using non-linear or linear regressions. Thereafter, the estimated parameters are further used to calculate their temperature dependence. Alternatively, a one-step method provides a regression fit to all experimental data sets, with the temperature dependence equation being directly built in the kinetic model. This fitting technique thus, (a) avoids the estimation of intermediate parameters and, (b) substantially increases the degrees of freedom and hence the precision of parameters’ estimates. Within this issue was further explored the logarithmic transformation of the mathematical equations used on the adequacy of the model to describe experimental data. In all cases non-weighted least-squares regression procedures were used. Both the examination and criticism of the current modelling strategies were done by assessing statistical data obtained, such as the confidence intervals of the estimates, correlation coefficients, sum of squares, and residuals normality

Experimental joint immobilization in guinea pigs. Effects on the knee joint

In young and adult guinea pigs, the aftermath experimentally induced by the immobilization of the knee joint in hyperextended forced position was studied. Joint immobilization which varied from one to nine weeks was attained by plaster. Eighty knee joints were examined macro and microscopically. Findings included: (1) muscular hypotrophy and joint stiffness in all animals, directly proportional to the length of immobilization; (2) haemoarthrosis in the first week; (3) intra-articular fibrous tissue proliferation ending up with fibrous ankylosis; (4) hyaline articular cartilage erosions; (5) various degrees of destructive menisci changes. A tentative explanation of the fibrous tissue proliferation and of the cartilage changes is offered

Quantiles for Fractions and Other Mixed Data

This paper studies the estimation of quantile regression for fractional data, focusing on the case where there are mass-points at zero or/and one. More generally, we propose a simple strategy for the estimation of the conditional quantiles of data from mixed distributions, which combines standard results on the estimation of censored and Box-Cox quantile regressions. The implementation of the proposed method is illustrated using a well-known dataset.

Darth Fader: Using wavelets to obtain accurate redshifts of spectra at very low signal-to-noise

We present the DARTH FADER algorithm, a new wavelet-based method for estimating redshifts of galaxy spectra in spectral surveys that is particularly adept in the very low SNR regime. We use a standard cross-correlation method to estimate the redshifts of galaxies, using a template set built using a PCA analysis on a set of simulated, noise-free spectra. Darth Fader employs wavelet filtering to both estimate the continuum & to extract prominent line features in each galaxy spectrum. A simple selection criterion based on the number of features present in the spectrum is then used to clean the catalogue: galaxies with fewer than six total features are removed as we are unlikely to obtain a reliable redshift estimate. Applying our wavelet-based cleaning algorithm to a simulated testing set, we successfully build a clean catalogue including extremely low signal-to-noise data (SNR=2.0), for which we are able to obtain a 5.1% catastrophic failure rate in the redshift estimates (compared with 34.5% prior to cleaning). We also show that for a catalogue with uniformly mixed SNRs between 1.0 & 20.0, with realistic pixel-dependent noise, it is possible to obtain redshifts with a catastrophic failure rate of 3.3% after cleaning (as compared to 22.7% before cleaning). Whilst we do not test this algorithm exhaustively on real data, we present a proof of concept of the applicability of this method to real data, showing that the wavelet filtering techniques perform well when applied to some typical spectra from the SDSS archive. The Darth Fader algorithm provides a robust method for extracting spectral features from very noisy spectra. The resulting clean catalogue gives an extremely low rate of catastrophic failures, even when the spectra have a very low SNR. For very large sky surveys, this technique may offer a significant boost in the number of faint galaxies with accurately determined redshifts.Comment: 22 pages, 15 figures. Accepted for publication in Astronomy & Astrophysic