Automated fragment identification for electron ionisation mass spectrometry: application to atmospheric measurements of halocarbons

Non-target screening consists in searching a sample for all present substances, suspected or unknown, with very little prior knowledge about the sample. This approach has been introduced more than a decade ago in the field of water analysis, together with dedicated compound identification tools, but is still very scarce for indoor and atmospheric trace gas measurements, despite the clear need for a better understanding of the atmospheric trace gas composition.For a systematic detection of emerging trace gases in the atmosphere, a new and powerful analytical method is gas chromatography (GC) of preconcentrated samples, followed by electron ionisation, high resolution mass spectrometry (EI-HRMS). In this work, we present data analysis tools to enable automated fragment formula annotation for unknown compounds measured by GC-EI-HRMS. Based on co-eluting mass/charge fragments, we developed an innovative data analysis method to reliably reconstruct the chemical formulae of the fragments, using efficient combinatorics and graph theory. The method does not require the presence of the molecular ion, which is absent in ~40% of EI spectra. Our method has been trained and validated on \textgreater50 halocarbons and hydrocarbons, with 3 to 20 atoms and molar masses of 30 to 330 g mol-1, measured with a mass resolution of approx.~3500. For 90% of the compounds, more than 90% of the annotated fragment formulae are correct. Cases of wrong identification can be attributed to the scarcity of detected fragments per compound or the lack of isotopic constraint (no minor isotopocule detected).Our method enables to reconstruct most probable chemical formulae independently from spectral databases. Therefore, it demonstrates the suitability of EI-HRMS data for non-target analysis and paves the way for the identification of substances for which no EI mass spectrum is registered in databases. We illustrate the performances of our method for atmospheric trace gases and suggest that it may be well suited for many other types of samples. The L-GPL licenced Python code is released under the name ALPINAC for ALgorithmic Process for Identification of Non-targeted Atmospheric Compounds.Comment: Journal of Cheminformatics, Chemistry Central Ltd. and BioMed Central, 202

David Hockney: The Yosemite Suite

Acidulées et singulières. Tels sont les premiers qualificatifs qui viennent à l’esprit lorsque l’on regarde les œuvres de la série Yosemite Suite de David Hockney. Le catalogue éponyme est édité à l’occasion de l’exposition à la Galerie Lelong (Paris, 20 mai-13 juillet 2017) et le lecteur avisé fera le lien avec la rétrospective consacrée à l’œuvre de l’artiste au Centre Pompidou (21 juin-23 octobre 2017). Avec un format vertical, l’artiste peint inlassablement des arbres jaunes et vert acide..

Unconstrained handwriting recognition applied to the processing of bank cheques

Develops a French and English database with a fully trainable word recognizer which bypasses the notion of character recognition

Computing Individual Discrete Logarithms Faster in GF(pn)GF(p^n)

The Number Field Sieve (NFS) algorithm is the best known method to compute discrete logarithms (DL) in finite fields $\mathbb{F}_{p^n}$, with $p$ medium to large and $n \geq 1$ small. This algorithm comprises four steps: polynomial selection, relation collection, linear algebra and finally, individual logarithm computation. The first step outputs two polynomials defining two number fields, and a map from the polynomial ring over the integers modulo each of these polynomials to $\mathbb{F}_{p^n}$. After the relation collection and linear algebra phases, the (virtual) logarithm of a subset of elements in each number field is known. Given the target element in $\mathbb{F}_{p^n}$, the fourth step computes a preimage in one number field. If one can write the target preimage as a product of elements of known (virtual) logarithm, then one can deduce the discrete logarithm of the target. As recently shown by the Logjam attack, this final step can be critical when it can be computed very quickly. But we realized that computing an individual DL is much slower in medium- and large-characteristic non-prime fields $\mathbb{F}_{p^n}$ with $n \geq 3$, compared to prime fields and quadratic fields $\mathbb{F}_{p^2}$. We optimize the first part of individual DL: the \emph{booting step}, by reducing dramatically the size of the preimage norm. Its smoothness probability is higher, hence the running-time of the booting step is much improved. Our method is very efficient for small extension fields with $2 \leq n \leq 6$ and applies to any $n > 1$, in medium and large characteristic

Valérie Mréjen : images en quête d’histoires

Une enveloppe cartonnée. A l’intérieur, trente-six photos en noir et blanc. Photos de famille, instants volés, portraits figés, sourires, solennité, exotisme ou familiarité. Des photos souvenirs qui pourraient être les nôtres et qui suscitent tour à tour l’amusement ou la nostalgie. Au dos, chaque photo est divisée en deux parties, comme une carte postale. En haut de chaque partie, un titre devancé d’un numéro. Et sous chaque titre une phrase. On comprend alors qu’il s’agit de remettre les ph..

A l’Ouest, toute ! Travailleuses de Bretagne et d’ailleurs (sous la dir. de Fabienne Dumont, Sylvie Ungauer)

« A l’Ouest, toute ! » est le résultat d’un travail initié par Fabienne Dumont et Sylvie Ungauer, toutes deux enseignantes à l’Ecole supérieure d’art de Bretagne – la première à Quimper et la seconde à Brest. Il fallut trois ans et la participation d’artistes et d’étudiants dans le cadre de différents ateliers, projections publiques, conférences, workshops et séminaires, pour faire évoluer et aboutir la réflexion des participants. Des artistes comme Margaret Harrison, Marie Preston ou Mierle ..