Spéciation chimique des éléments traces métalliques dans un environnement lagunaire confiné: La baie de Bietry

L’analyse des concentrations métalliques déterminées pour les sédiments de la baie de Biétry a permis d’évaluer le niveau de pollution. Les métaux non pollués (classe 0 et 1) sont : Th, Co, V, Ni, Ag et Sb, avec des proportions qui varient de 55 à 70%. Les métaux pollués (classes 2, 3, 5, 6) présentent des proportions variant de 100 à 70%. Il s’agit de Cr, Mo, As, U, Pb, Cd, Zn et Cu. Les résultats des extractions sélectives effectuées ont permis de déterminer le potentiel de mobilité et de disponibilité biologique de ces ETM (Eléments Traces Métalliques) polluants. Ainsi le gradient de biodisponibilité dans la baie de Biétry s’établit comme suit: Ni>Co>Zn et dans une moindre mesure V>Cu>As>Th>Mo>Pb>Sb. Dans les phases porteuses des ETM, la fraction résiduelle est la plus dominante pour tous les métaux à l’exception de Zn et Mo. Du polluant le plus mobile au moins mobile, nous avons obtenu l’ordre suivant: Zn, Ni, Pb, Co, Th, Mo, As, Sb, Cr.Mots clés: Igeo, pollution, biodisponibilité, spéciation métalliqu

Violation of the phase space general covariance as a diffeomorphism anomaly in quantum mechanics

We consider a topological quantum mechanics described by a phase space path integral and study the 1-dimensional analog for the path integral representation of the Kontsevich formula. We see that the naive bosonic integral possesses divergences, that it is even naively non-invariant and thus is ill-defined. We then consider a super-extension of the theory which eliminates the divergences and makes the theory naively invariant. This super-extension is equivalent to the correct choice of measure and was discussed in the literature. We then investigate the behavior of this extended theory under diffeomorphisms of the extended phase space and despite of its naive invariance find out that the theory possesses anomaly under nonlinear diffeomorphisms. We localize the origin of the anomaly and calculate the lowest nontrivial anomalous contribution.Comment: 36 page

Improvement of structure and quality of nanoscale multilayered composite coatings, deposited by filtered cathodic vacuum arc deposition method

This article studies the specific features of cathode vacuum arc deposition of coatings used in the production of cutting tools. The detailed analysis of the major drawbacks of arc-Physical Vapour Deposition (PVD) methods has contributed to the development of the processes of filtered cathodic vacuum arc deposition to form nanoscale multilayered composite coatings of increased efficiency. This is achieved through the formation of nanostructure, increase in strength of adhesion of coating to substrate up to 20%, and reduction of such dangerous coating surface defects as macro- and microdroplets up to 80%. This article presents the results of the studies of various properties of developed nanoscale multilayered composite coating. The certification tests of carbide tool equipped with cutting inserts with developed nanoscale multilayered composite coating compositions in longitudinal turning (continuous cutting) and end symmetric milling, and intermittent cutting of steel C45 and hard-to-cut nickel alloy of NiCr20TiAl showed advantages of tool with nanoscale multilayered composite coating as compared to the tool without coating. The lifetime of the carbide inserts with developed NMCC based on the system of Ti-TiN-(NbZrTiCr)N (filtered cathodic vacuum arc deposition) was increased up to 5-6 times in comparison with the control tools without coatings and up to 1.5-2.0 times in comparison with nanoscale multilayered composite coating based on the system of Ti-TiN-(NbZrTiCr)N (standard arc-PVD technology). © The Author(s) 2017

Interaction of silicon dangling bonds with insulating surfaces

We use first principles density functional theory calculations to study the interaction of a model dangling bond silicon tip with the surfaces of CaF2, Al2O3, TiO2, and MgO. In each case the strongest interaction is with the highest anions in the surface. We show that this is due to the onset of chemical bonding with the surface anions, which can be controlled by an electric field across the system. Combining our results and previous studies on semiconductor surfaces suggests that using dangling bond Si tips can provide immediate identification of surface species in atomically resolved noncontact atomic force microscopy and facilitate selective measurements of short-range interactions with surface sites

Integrated information increases with fitness in the evolution of animats

One of the hallmarks of biological organisms is their ability to integrate disparate information sources to optimize their behavior in complex environments. How this capability can be quantified and related to the functional complexity of an organism remains a challenging problem, in particular since organismal functional complexity is not well-defined. We present here several candidate measures that quantify information and integration, and study their dependence on fitness as an artificial agent ("animat") evolves over thousands of generations to solve a navigation task in a simple, simulated environment. We compare the ability of these measures to predict high fitness with more conventional information-theoretic processing measures. As the animat adapts by increasing its "fit" to the world, information integration and processing increase commensurately along the evolutionary line of descent. We suggest that the correlation of fitness with information integration and with processing measures implies that high fitness requires both information processing as well as integration, but that information integration may be a better measure when the task requires memory. A correlation of measures of information integration (but also information processing) and fitness strongly suggests that these measures reflect the functional complexity of the animat, and that such measures can be used to quantify functional complexity even in the absence of fitness data.Comment: 27 pages, 8 figures, one supplementary figure. Three supplementary video files available on request. Version commensurate with published text in PLoS Comput. Bio

Causal blankets : Theory and algorithmic framework

Funding Information: F.R. was supported by the Ad Astra Chandaria foundation. P.M. was funded by the Wellcome Trust (grant no. 210920/Z/18/Z). M.B. was supported by a grant from Tem-pleton World Charity Foundation, Inc. (TWCF). The opinions expressed in this publication are those of the authors and do not necessarily reflect the views of TWCF. Publisher Copyright: © 2020, Springer Nature Switzerland AG. This is a post-peer-review, pre-copyedit version of Rosas, F. E., Mediano, P. A. M., Biehl, M., Chandaria, S., & Polani, D. (2020). Causal blankets: Theory and algorithmic framework. In T. Verbelen, P. Lanillos, C. L. Buckley, & C. De Boom (Eds.), Active Inference - First International Workshop, IWAI 2020, Co-located with ECML/PKDD 2020, Proceedings (pp. 187-198). (Communications in Computer and Information Science; Vol. 1326). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-3-030-64919-7_19We introduce a novel framework to identify perception-action loops (PALOs) directly from data based on the principles of computational mechanics. Our approach is based on the notion of causal blanket, which captures sensory and active variables as dynamical sufficient statistics—i.e. as the “differences that make a difference.” Furthermore, our theory provides a broadly applicable procedure to construct PALOs that requires neither a steady-state nor Markovian dynamics. Using our theory, we show that every bipartite stochastic process has a causal blanket, but the extent to which this leads to an effective PALO formulation varies depending on the integrated information of the bipartition

Matrix Model Conjecture for Exact BS Periods and Nekrasov Functions

We give a concise summary of the impressive recent development unifying a number of different fundamental subjects. The quiver Nekrasov functions (generalized hypergeometric series) form a full basis for all conformal blocks of the Virasoro algebra and are sufficient to provide the same for some (special) conformal blocks of W-algebras. They can be described in terms of Seiberg-Witten theory, with the SW differential given by the 1-point resolvent in the DV phase of the quiver (discrete or conformal) matrix model (\beta-ensemble), dS = ydz + O(\epsilon^2) = \sum_p \epsilon^{2p} \rho_\beta^{(p|1)}(z), where \epsilon and \beta are related to the LNS parameters \epsilon_1 and \epsilon_2. This provides explicit formulas for conformal blocks in terms of analytically continued contour integrals and resolves the old puzzle of the free-field description of generic conformal blocks through the Dotsenko-Fateev integrals. Most important, this completes the GKMMM description of SW theory in terms of integrability theory with the help of exact BS integrals, and provides an extended manifestation of the basic principle which states that the effective actions are the tau-functions of integrable hierarchies.Comment: 14 page

Using genetic algorithms to generate test sequences for complex timed systems

The generation of test data for state based specifications is a computationally expensive process. This problem is magnified if we consider that time con- straints have to be taken into account to govern the transitions of the studied system. The main goal of this paper is to introduce a complete methodology, sup- ported by tools, that addresses this issue by represent- ing the test data generation problem as an optimisa- tion problem. We use heuristics to generate test cases. In order to assess the suitability of our approach we consider two different case studies: a communication protocol and the scientific application BIPS3D. We give details concerning how the test case generation problem can be presented as a search problem and automated. Genetic algorithms (GAs) and random search are used to generate test data and evaluate the approach. GAs outperform random search and seem to scale well as the problem size increases. It is worth to mention that we use a very simple fitness function that can be eas- ily adapted to be used with other evolutionary search techniques

Forecasting future Humphrey Visual Fields using deep learning

Purpose To determine if deep learning networks could be trained to forecast future 24–2 Humphrey Visual Fields (HVFs). Methods All data points from consecutive 24–2 HVFs from 1998 to 2018 were extracted from a university database. Ten-fold cross validation with a held out test set was used to develop the three main phases of model development: model architecture selection, dataset combination selection, and time-interval model training with transfer learning, to train a deep learning artificial neural network capable of generating a point-wise visual field prediction. The pointwise mean absolute error (PMAE) and difference in Mean Deviation (MD) between predicted and actual future HVF were calculated. Results More than 1.7 million perimetry points were extracted to the hundredth decibel from 32,443 24–2 HVFs. The best performing model with 20 million trainable parameters, CascadeNet- 5, was selected. The overall point-wise PMAE for the test set was 2.47 dB (95% CI: 2.45 dB to 2.48 dB), and deep learning showed a statistically significant improvement over linear models. The 100 fully trained models successfully predicted future HVFs in glaucomatous eyes up to 5.5 years in the future with a correlation of 0.92 between the MD of predicted and actual future HVF and an average difference of 0.41 dB. Conclusions Using unfiltered real-world datasets, deep learning networks show the ability to not only learn spatio-temporal HVF changes but also to generate predictions for future HVFs up to 5.5 years, given only a single HVF

About intrinsic transversality of pairs of sets

The article continues the study of the ‘regular’ arrangement of a collection of sets near a point in their intersection. Such regular intersection or, in other words, transversality properties are crucial for the validity of qualification conditions in optimization as well as subdifferential, normal cone and coderivative calculus, and convergence analysis of computational algorithms. One of the main motivations for the development of the transversality theory of collections of sets comes from the convergence analysis of alternating projections for solving feasibility problems. This article targets infinite dimensional extensions of the intrinsic transversality property introduced recently by Drusvyatskiy, Ioffe and Lewis as a sufficient condition for local linear convergence of alternating projections. Several characterizations of this property are established involving new limiting objects defined for pairs of sets. Special attention is given to the convex case