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Chloramphenicol (CAP) is a broad‐spectrum antibiotic widely used in animal farming and aquaculture industries. Despite its ban in many countries around the world, it is still used in several developing countries, with harmful effects on the surrounding aquatic environment. In this study, an electrooxidation process using a Ti/PbO2anode was used to investigate the degradation of CAP in both synthetic solution and real aquaculture wastewater. A central composite design was used to determine the optimum conditions for CAP removal. Current intensity and treatment time had the most impact on the CAP removal. These two factors accounted for ∼90% of CAP removal. The optimum conditions found in this study were current intensity of 0.65 A, treatment time of 34 min, and CAP initial concentration of 0.5 mg L−1. Under these conditions, 98.7% of CAP removal was achieved with an energy consumption of 4.65 kW h−1m−3. The antibiotic was not present in the aquaculture wastewater, which received 0.5 mg L−1of CAP and was treated (by electrooxidation) under the optimum conditions. A complete removal of CAP was obtained after 34 min of treatment. According to these results, electrooxidation presents an option for the removal of antibiotics, secondary compounds, and other organic and inorganic compounds from solution. Antibiotics cause microbial resistance.Electrooxidation removes antibiotics.

We consider the estimation of the regularization parameter for the simultaneous deblurring of multiple noisy images via Tikhonov regularization. We approach the problem in three ways. We first reduce the problem to a single-image deblurring for which the regularization parameter can be estimated through a classic generalized cross-validation (${\rm GCV}$) method. A modification of this function is used for correcting the undersmoothing typical of the original technique. With a second method, we minimize an average least-squares fit to the images and define a new ${\rm GCV}$function. In the last approach, we use the classical ${\rm GCV}$on a single higher-dimensional image obtained by concatenating all the images into a single vector. With a reliable estimator of the regularization parameter, one can fully exploit the excellent computational characteristics typical of direct deblurring methods, which, especially for large images, makes them competitive with the more flexible but much slower iterative algorithms. The performance of the techniques is analyzed through numerical experiments. We find that under the independent homoscedastic and Gaussian assumptions made on the noise, the three approaches provide almost identical results with the first single image providing the practical advantage that no new software is required and the same image can be used with other deblurring algorithms.

We consider the simultaneous deblurring of a set of noisy images whose point spread functions are different but known and spatially invariant, and with Gaussian noise. Currently available iterative algorithms that are typically used for this type of problem are computationally expensive, which makes their application for very large images impractical. We present a simple extension of a classical least-squares (LS) method where the multi-image deblurring is efficiently reduced to a computationally efficient single-image deblurring. In particular, we show that it is possible to remarkably improve the ill-conditioning of the LS problem by means of stable operations on the corresponding normal equations, which in turn speed up the convergence rate of the iterative algorithms. The performance and limitations of the method are analyzed through numerical simulations. Its connection with a column weighted least-squares approach is also considered in an appendix.

In this second paper in a series dedicated to developing efficient numerical techniques for the deblurring Cosmic Microwave Background (CMB) maps, we consider the case of asymmetric point spread functions (PSF). Although conceptually this problem is not different from the symmetric case, there are important differences from the computational point of view because it is no longer possible to use some of the efficient numerical techniques that work with symmetric PSFs. We present procedures that permit the use of efficient techniques even when this condition is not met. In particular, two methods are considered: a procedure based on a Kronecker approximation technique that can be implemented with the numerical methods used with symmetric PSFs but that has the limitation of requiring only mildly asymmetric PSFs. The second is a variant of the classic Tikhonov technique that works even with very asymmetric PSFs but that requires discarding the edges of the maps. We provide details for efficient implementations of the algorithms. Their performance is tested on simulated CMB maps.

Digital deblurring of images is an important problem that arises in multifrequency observations of the Cosmic Microwave Background (CMB) where, because of the width of the point spread functions (PSF), maps at different frequencies suffer a different loss of spatial resolution. Deblurring is useful for various reasons: first, it helps to restore high frequency components lost through the smoothing effect of the instrument's PSF; second, emissions at various frequencies observed with different resolutions can be better studied on a comparable resolution; third, some map-based component separation algorithms require maps with similar level of degradation. Because of computational efficiency, deblurring is usually done in the frequency domain. But this approach has some limitations as it requires spatial invariance of the PSF, stationarity of the noise, and is not flexible in the selection of more appropriate boundary conditions. Deblurring in real space is more flexible but usually not used because of its high computational cost. In this paper (the first in a series on the subject) we present new algorithms that allow the use of real space deblurring techniques even for very large images. In particular, we consider the use of Tikhonov deblurring of noisy maps with applications to PLANCK. We provide details for efficient implementations of the algorithms. Their performance is tested on Gaussian and non-Gaussian simulated CMB maps, and PSFs with both circular and elliptical symmetry. Matlab code is made available.

Point-source contamination in high-precision Cosmic Microwave Background (CMB) maps severely affects the precision of cosmological parameter estimates. Among the methods that have been proposed for source detection, the family of pseudo-filters optimizes a measure of signal-to-noise and amplitude-scale relation. In this paper we show that these filters are in fact only restrictive cases of a more general class of matched filters that optimize signal-to-noise ratio and that have, in general, better source detection capabilities, especially for lower amplitude sources. These conclusions are confirmed by some numerical experiments.

The purpose of this study was to evaluate the incidence and etiology of bacterial and fungal infection or contamination in lung allograft donors and to assess donor-to-host transmission of these infections. Recipients who survived more than 24 h and their respective donors were evaluated. The overall incidence of donor infection was 52% (103 out of 197 donors). Types of donor infection included isolated contamination of preservation fluids (n = 30, 29.1%), graft colonization (n = 65, 63.1%) and bacteremia (n = 8, 7.8%). Donor-to-host transmission of bacterial or fungal infection occurred in 15 lung allograft recipients, 7.6% of lung transplants performed. Among these cases, 2 were due to donor bacteremia and 13 to colonization of the graft. Twenty-five percent of donors with bacteremia and 14.1% of colonized grafts were responsible for transmitting infection. Excluding the five cases without an effective prophylactic regimen, prophylaxis failure occurred in 11 out of 197 procedures (5.58%). Donor-to-host transmission of infection is a frequent event after lung transplantation. Fatal consequences can be avoided with an appropriate prophylactic antibiotic regimen that must be modified according to the microorganisms isolated from cultures of samples obtained from donors, grafts, preservation fluids and recipients.

The purpose of this study was to evaluate the incidence and etiology of bacterial and fungal infection or contamination in lung allograft donors and to assess donor-to-host transmission of these infections. Recipients who survived more than 24 h and their respective donors were evaluated. The overall incidence of donor infection was 52% (103 out of 197 donors). Types of donor infection included isolated contamination of preservation fluids (n = 30, 29.1%), graft colonization (n = 65, 63.1%) and bacteremia (n = 8, 7.8%). Donor-to-host transmission of bacterial or fungal infection occurred in 15 lung allograft recipients, 7.6% of lung transplants performed. Among these cases, 2 were due to donor bacteremia and 13 to colonization of the graft. Twenty-five percent of donors with bacteremia and 14.1% of colonized grafts were responsible for transmitting infection. Excluding the five cases without an effective prophylactic regimen, prophylaxis failure occurred in 11 out of 197 procedures (5.58%). Donor-to-host transmission of infection is a frequent event after lung transplantation. Fatal consequences can be avoided with an appropriate prophylactic antibiotic regimen that must be modified according to the microorganisms isolated from cultures of samples obtained from donors, grafts, preservation fluids and recipients.

The sky rms is the simplest model-independent characterization of a cosmological anisotropy signal. We show that the rms temperature fluctuations determined from the COBEDifferential Microwave Radiometer (DMR) 4 yr sky maps are frequency independent, consistent with the Planckian spectrum expected for the cosmic microwave background signal and therefore with the hypothesis that they are cosmological in origin. The typical rms amplitude is ~35 ± 2 ?K at 7° and ~29 ± 1 ?K at 10°. An analysis of the rms anisotropy determined from the data in both Galactic and ecliptic coordinates is used to determine the rms quadrupole normalization, Qrms-PS, for a scale-invariant Harrison-Zeldovich power-law model. Corrections are applied for small biases observed in the likelihood analysis. While there are variations depending on the data selection, all results are consistent with a Qrms-PSnormalization of ~18 ± 2 ?K. This is also shown to be true for a "standard" cold dark matter model of cosmological anisotropy. The difference in the normalization amplitudes derived when the quadrupole is either included or excluded from the analysis is attributable to contamination of the observed sky quadrupole by foreground Galactic emission.