Analytical and mathematical methods for revealing hidden details in ancient manuscripts and paintings: A review

In this work, a critical review of the current nondestructive probing and image analysis approaches is presented, to revealing otherwise invisible or hardly discernible details in manuscripts and paintings relevant to cultural heritage and archaeology. Multispectral imaging, X-ray fluorescence, Laser-Induced Breakdown Spectroscopy, Raman spectroscopy and Thermography are considered, as techniques for acquiring images and spectral image sets; statistical methods for the analysis of these images are then discussed, including blind separation and false colour techniques. Several case studies are presented, with particular attention dedicated to the approaches that appear most promising for future applications. Some of the techniques described herein are likely to replace, in the near future, classical digital photography in the study of ancient manuscripts and paintings

Separation of Dependent Sources in Astrophysical Radiation Maps using Second Order Statistics

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Neural networks and separation of Cosmic Microwave Background and astrophysical signals in sky maps

The Independent Component Analysis (ICA) algorithm is implemented as a neural network for separating signals of different origin in astrophysical sky maps. Due to its self-organizing capability, it works without prior assumptions on the signals, neither on their frequency scaling, nor on the signal maps themselves; instead, it learns directly from the input data how to separate the physical components, making use of their statistical independence. To test the capabilities of this approach, we apply the ICA algorithm on sky patches, taken from simulations and observations, at the microwave frequencies, that are going to be deeply explored in a few years on the whole sky, by the Microwave Anisotropy Probe (MAP) and by the {\sc Planck} Surveyor Satellite. The maps are at the frequencies of the Low Frequency Instrument (LFI) aboard the {\sc Planck} satellite (30, 44, 70 and 100 GHz), and contain simulated astrophysical radio sources, Cosmic Microwave Background (CMB) radiation, and Galactic diffuse emissions from thermal dust and synchrotron. We show that the ICA algorithm is able to recover each signal, with precision going from 10% for the Galactic components to percent for CMB; radio sources are almost completely recovered down to a flux limit corresponding to $0.7\sigma_{CMB}$, where $\sigma_{CMB}$ is the rms level of CMB fluctuations. The signal recovering possesses equal quality on all the scales larger then the pixel size. In addition, we show that the frequency scalings of the input signals can be partially inferred from the ICA outputs, at the percent precision for the dominant components, radio sources and CMB.Comment: 15 pages; 6 jpg and 1 ps figures. Final version to be published in MNRA

Immunogold electron microscopic evidence of in situ formation of homo- and heteromeric purinergic adenosine A1 and P2Y2 receptors in rat brain

<p>Abstract</p> <p>Background</p> <p>Purines such as adenosine and ATP are now generally recognized as the regulators of many physiological functions, such as neurotransmission, pain, cardiac function, and immune responses. Purines exert their functions via purinergic receptors, which are divided into adenosine and P2 receptors. Recently, we demonstrated that the G_i/o-coupled adenosine A₁receptor (A₁R) and G_q/11-coupled P2Y₂receptor (P2Y₂R) form a heteromeric complex with unique pharmacology in co-transfected human embryonic kidney cells (HEK293T). However, the heteromeric interaction of A₁R and P2Y₂R <it>in situ </it>in brain is still largely unknown.</p> <p>Findings</p> <p>In the present study, we visualized the surface expression and co-localization of A₁R and P2Y₂R in both transfected HEK293T cells and in rat brain by confocal microscopy and more precisely by immunogold electron microscopy. Immunogold electron microscopy showed the evidence for the existence of homo- and hetero-dimers among A₁R and P2Y₂R at the neurons in cortex, cerebellum, and particularly cerebellar Purkinje cells, also supported by co-immunoprecipitation study.</p> <p>Conclusion</p> <p>The results suggest that evidence for the existence of homo- and hetero-dimers of A₁R and P2Y₂R, not only in co-transfected cultured cells, but also <it>in situ </it>on the surface of neurons in various brain regions. While the homo-dimerization ratios displayed similar patterns in all three regions, the rates of hetero-dimerization were prominent in hippocampal pyramidal cells among the three regions.</p

Planck pre-launch status : The Planck mission

Peer reviewe

Using Non-Negative Matrix Factorization for Removing Show-Through

BN 978-3-642-15994-7, SoftcoverInternational audienceScanning process usually degrades digital documents due to the contents of the backside of the scanned manuscript. This is often because of the show-through effect, i.e. the backside image that interferes with the main front side picture mainly due to the intrinsic transparency of the paper used for printing or writing. In this paper, we first use one of Non-negative Matrix Factorization (NMF) methods for canceling show-through phenomenon. Then, nonlinearity of show-through effect is included by changing the cost function used in this method. Simulation results show that this proposed algorithm can remove show-through effectively

On the resolution properties of a particular tomographic technique for industrial testing using ultrasounds or micro waves

Dans ce travail on étudie les propriétés d'une particulière technique de tomographie cohérente basée sur le traitement du champ rétrodiffusé par le corps qui doit être examiné. On assume que le corps, homogène et avec les mêmes carathéristiques électromagnétiques du milieu environnant, contient deux points irradiateurs à distance D entre eux; en se rapportant à cette condition expérimentale, on étudie le pouvoir de résolution du méthode tomographic examiné, dans le cas où on emploie des micro-ondes ou des ultra-sons pour explorer le corps. Après avoir défini un convenable Facteur de Séparation S, on dérive, pour différentes valeurs de D, des mappes dans lesquelles S dépend des valeurs de la fréquence centrale et de la largeur de la bande des fréquences employées dans la mesure