Spaceability in Banach and quasi-Banach sequence spaces

Let $X$ be a Banach space. We prove that, for a large class of Banach or quasi-Banach spaces $E$ of $X$-valued sequences, the sets $E-\bigcup _{q\in\Gamma}\ell_{q}(X)$, where $\Gamma$ is any subset of $(0,\infty]$, and $E-c_{0}(X)$ contain closed infinite-dimensional subspaces of $E$ (if non-empty, of course). This result is applied in several particular cases and it is also shown that the same technique can be used to improve a result on the existence of spaces formed by norm-attaining linear operators.Comment: 9 page

On a Gibbs sampler based random process in Bayesian nonparametrics

We define and investigate a new class of measure-valued Markov chains by resorting to ideas formulated in Bayesian nonparametrics related to the Dirichlet process and the Gibbs sampler. Dependent random probability measures in this class are shown to be stationary and ergodic with respect to the law of a Dirichlet process and to converge in distribution to the neutral diffusion model.Random probability measure; Dirichlet process; Blackwell-MacQueen Pólya urn scheme; Gibbs sampler; Bayesian nonparametrics

Fast method for the determination of short-chain-length polyhydroxyalkanoates (scl-PHAs) in bacterial samples by In Vial-Thermolysis (IVT)

none8siA new method based on the GC–MS analysis of thermolysis products obtained by treating bacterial samples at a high temperature (above 270 C) has been developed. This method, here named “In-Vial- Thermolysis” (IVT), allowed for the simultaneous determination of short-chain-length polyhydrox- yalkanoates (scl-PHA) content and composition. The method was applied to both single strains and microbial mixed cultures (MMC) fed with different carbon sources. The IVT procedure provided similar analytical performances compared to previous Py-GC–MS and Py- GC-FID methods, suggesting a similar application for PHA quantitation in bacterial cells. Results from the IVT procedure and the traditional methanolysis method were compared; the correlation between the two datasets was fit for the purpose, giving a R2 of 0.975. In search of further simplification, the rationale of IVT was exploited for the development of a “field method” based on the titration of thermolyzed samples with sodium hydrogen carbonate to quantify PHA inside bacterial cells. The accuracy of the IVT method was fit for the purpose. These results lead to the possibility for the on-line measurement of PHA productivity. Moreover, they allow for the fast and inexpensive quantification/characterization of PHA for biotechnological process control, as well as investigation over various bacterial communities and/or feeding strategies.mixedF. Abbondanzi; G. Biscaro; G. Carvalho; L. Favaro; P. Lemos; M. Paglione; C. Samorì; C. TorriF. Abbondanzi; G. Biscaro; G. Carvalho; L. Favaro; P. Lemos; M. Paglione; C. Samorì; C. Torr

A class of measure-valued Markov chains and Bayesian nonparametrics

Measure-valued Markov chains have raised interest in Bayesian nonparametrics since the seminal paper by (Math. Proc. Cambridge Philos. Soc. 105 (1989) 579--585) where a Markov chain having the law of the Dirichlet process as unique invariant measure has been introduced. In the present paper, we propose and investigate a new class of measure-valued Markov chains defined via exchangeable sequences of random variables. Asymptotic properties for this new class are derived and applications related to Bayesian nonparametric mixture modeling, and to a generalization of the Markov chain proposed by (Math. Proc. Cambridge Philos. Soc. 105 (1989) 579--585), are discussed. These results and their applications highlight once again the interplay between Bayesian nonparametrics and the theory of measure-valued Markov chains.Comment: Published in at http://dx.doi.org/10.3150/11-BEJ356 the Bernoulli (http://isi.cbs.nl/bernoulli/) by the International Statistical Institute/Bernoulli Society (http://isi.cbs.nl/BS/bshome.htm

Motion deblurring of faces

Face analysis is a core part of computer vision, in which remarkable progress has been observed in the past decades. Current methods achieve recognition and tracking with invariance to fundamental modes of variation such as illumination, 3D pose, expressions. Notwithstanding, a much less standing mode of variation is motion deblurring, which however presents substantial challenges in face analysis. Recent approaches either make oversimplifying assumptions, e.g. in cases of joint optimization with other tasks, or fail to preserve the highly structured shape/identity information. Therefore, we propose a data-driven method that encourages identity preservation. The proposed model includes two parallel streams (sub-networks): the first deblurs the image, the second implicitly extracts and projects the identity of both the sharp and the blurred image in similar subspaces. We devise a method for creating realistic motion blur by averaging a variable number of frames to train our model. The averaged images originate from a 2MF2 dataset with 10 million facial frames, which we introduce for the task. Considering deblurring as an intermediate step, we utilize the deblurred outputs to conduct a thorough experimentation on high-level face analysis tasks, i.e. landmark localization and face verification. The experimental evaluation demonstrates the superiority of our method

Endoglin (CD105) is not a specific selection marker for endothelial cells in human islets of Langerhans. Reply to Wheeler-Jones CPD, Clarkin CE, Farrar CE et al [letter]

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