A Rapid, Empirical Method for Detection and Estimation of Outlier Frames in Particle Imaging Velocimetry Data using Proper Orthogonal Decomposition

This paper develops a method for detection and removal of outlier images from digital Particle Image Velocimetry data using Proper Orthogonal De-composition (POD). The outlier is isolated in the leading POD modes, removed and a replacement value re-estimated. The method is used to estimate and replace whole images within the sequence. This is particularly useful, if a single PIV image is suddenly heavily contaminated with background noise, or to estimate a dropped frame within a sequence. The technique is tested on a synthetic dataset that permits the effective acquisition frequency to be varied systematically, before application to flow field frames obtained from a large-eddy simulation. As expected, outlier re-estimation becomes more difficult when the integral time scale for the flow is long relative to the sampling period. However, the method provides a systematic improvement in predicting frames compared to interpolating from neighbouring(1) frames

A rapid non-iterative proper orthogonal decomposition based outlier detection and correction for PIV data

The present work proposes a novel method of detection and estimation of outliers in particle image velocimetry measurements by the modification of the temporal coefficients associated with a proper orthogonal decomposition of an experimental time series. Using synthetic outliers applied to two sequences of vector fields, the method is benchmarked against stateof-the-art approaches recently proposed to remove the influence of outliers. Compared with these methods, the proposed approach offers an increase in accuracy and robustness for the detection of outliers and comparable accuracy for their estimation

Large-scale optimization with the primal-dual column generation method

The primal-dual column generation method (PDCGM) is a general-purpose column generation technique that relies on the primal-dual interior point method to solve the restricted master problems. The use of this interior point method variant allows to obtain suboptimal and well-centered dual solutions which naturally stabilizes the column generation. As recently presented in the literature, reductions in the number of calls to the oracle and in the CPU times are typically observed when compared to the standard column generation, which relies on extreme optimal dual solutions. However, these results are based on relatively small problems obtained from linear relaxations of combinatorial applications. In this paper, we investigate the behaviour of the PDCGM in a broader context, namely when solving large-scale convex optimization problems. We have selected applications that arise in important real-life contexts such as data analysis (multiple kernel learning problem), decision-making under uncertainty (two-stage stochastic programming problems) and telecommunication and transportation networks (multicommodity network flow problem). In the numerical experiments, we use publicly available benchmark instances to compare the performance of the PDCGM against recent results for different methods presented in the literature, which were the best available results to date. The analysis of these results suggests that the PDCGM offers an attractive alternative over specialized methods since it remains competitive in terms of number of iterations and CPU times even for large-scale optimization problems.Comment: 28 pages, 1 figure, minor revision, scaled CPU time

Ubiquitous influenza A virus in Chilean swine before the H1N1pdm09 introduction.

Influenza A virus (IAV) was a neglected swine pathogen in South America before the 2009 H1N1 pandemic (A(H1N1)pdm2009). The A(H1N1)pdm2009 strain has widely spread among the Chilean swine population and co-circulates with endemic H1N2 and H3N2 viruses. The presence of IAV as a swine pathogen in Chilean swine before the 2009 pandemic is unknown. To understand the IAV in swine prior to 2009, aY retrospective study of samples from pigs affected with respiratory diseases was conducted. Ninety formalin-fixed and paraffin-embedded lung tissues belonging to 21 intensive pig production companies located in five different administrative regions of Chile, collected between 2005 and 2008, were evaluated. The tissues were tested by immunohistochemistry (IHC), identifying that 9 out of 21 farms (42.8%) and 31 out of 90 (34.4%) samples were IAV positive. Only three out of the 31 IHC-positive samples were positive upon RNA extraction and rtRT-PCR analysis. Partial nucleotide sequences were obtained from one sample and characterized as an H3N2 subtype closely related to a human seasonal H3N2 IAVs that circulated globally in the mid-90s. These results indicate that IAV was circulating in swine before 2009 and highlight the value of conducting retrospective studies through genomic strategies to analyse historical samples

Swedish spring wheat varieties with the rare high grain protein allele of NAM-B1 differ in leaf senescence and grain mineral content

Some Swedish spring wheat varieties have recently been shown to carry a rare wildtype (wt) allele of the gene NAM-B1, known to affect leaf senescence and nutrient retranslocation to the grain. The wt allele is believed to increase grain protein concentration and has attracted interest from breeders since it could contribute to higher grain quality and more nitrogen-efficient varieties. This study investigated whether Swedish varieties with the wt allele differ from varieties with one of the more common, non-functional alleles in order to examine the effect of the gene in a wide genetic background, and possibly explain why the allele has been retained in Swedish varieties. Forty varieties of spring wheat differing in NAM-B1 allele type were cultivated under controlled conditions. Senescence was monitored and grains were harvested and analyzed for mineral nutrient concentration. Varieties with the wt allele reached anthesis earlier and completed senescence faster than varieties with the non-functional allele. The wt varieties also had more ears, lighter grains and higher yields of P and K. Contrary to previous information on effects of the wt allele, our wt varieties did not have increased grain N concentration or grain N yield. In addition, temporal studies showed that straw length has decreased but grain N yield has remained unaffected over a century of Swedish spring wheat breeding. The faster development of wt varieties supports the hypothesis of NAM-B1 being preserved in Fennoscandia, with its short growing season, because of accelerated development conferred by the NAM-B1 wt allele. Although the possible effects of other gene actions were impossible to distinguish, the genetic resource of Fennoscandian spring wheats with the wt NAM-B1 allele is interesting to investigate further for breeding purposes

The Temporal and Spatial Evolution of Magnetohydrodynamic Wave Modes in Sunspots

Through their lifetime, sunspots undergo a change in their area and shape and, as they decay, they fragment into smaller structures. Here, for the first time we analyze the spatial structure of the magnetohydrodynamic (MHD) slow-body and fast-surface modes in the observed umbrae as their cross-sectional shape changes. The proper orthogonal decomposition (POD) and dynamic mode decomposition (DMD) techniques were used to analyze 3 and 6 hr Solar Dynamics Observatory/Helioseismic and Magnetic Imager time series of Doppler velocities at the photospheric level of approximately circular and elliptically shaped sunspots. Each time series was divided into equal time intervals to evidence the change in the shape of the sunspots. To identify the physical wave modes, the POD/DMD modes were cross-correlated with a slow-body mode model using the exact shape of the umbra, whereas the shape obtained by applying a threshold level of the mean intensity for every time interval. Our results show that the spatial structure of MHD modes are affected, even by apparently small changes in the umbral shape, especially in the case of the higher-order modes. For the data sets used in our study, the optimal time intervals to consider the influence of the change in the shape on the observed MHD modes is 37–60 minutes. The choice of these intervals is crucial to properly quantify the energy contribution of each wave mode to the power spectrum