Production of biofuels and biomolecules in the framework of circular economy: A regional case study

peer reviewedFaced to the economic and energetic context of our society, it is widely recognised that an alternative to fossil fuels and oil-based products will be needed in the nearest future. In this way, development of urban biorefinery could bring many solutions to this problem. Study of the implementation of urban biorefinery highlights two sustainable configurations that provide solutions to the Walloon context by promoting niche markets, developing circular economy and reducing transport of supply feedstock. First, autonomous urban biorefineries are proposed, which use biological waste for the production of added value molecules and/or finished products and are energetically self-sufficient. Second,integrated urban biorefineries, which benefit from an energy supply from a nearby industrial activity. In the Walloon economic context, these types of urban biorefineries could provide solutions by promoting niche markets, developing a circular economy model, optimise the transport of supply feedstock and contribute to the sustainable development

Single-scan skeletonization driven by a neighborhood-sequence distance

International audienceShape description is an important step in image analysis. Skeletonization methods are widely used in image analysis as they are a powerful tool to describe a shape. Indeed, a skeleton is a one point wide line centered in the shape which keeps the shape's topology. Commonly, at least two scans of the image are needed for the skeleton computation in the state of art methods of skeletonization. In this work, a single scan is used considering information propagation in order to compute the skeleton. This paper presents also a new single-scan skeletonization using different distances likes d4, d8 and dns

On the Testing of Ground--Motion Prediction Equations against Small--Magnitude Data

Ground-motion prediction equations (GMPE) are essential in probabilistic seismic hazard studies for estimating the ground motions generated by the seismic sources. In low seismicity regions, only weak motions are available in the lifetime of accelerometric networks, and the equations selected for the probabilistic studies are usually models established from foreign data. Although most ground-motion prediction equations have been developed for magnitudes 5 and above, the minimum magnitude often used in probabilistic studies in low seismicity regions is smaller. Desaggregations have shown that, at return periods of engineering interest, magnitudes lower than 5 can be contributing to the hazard. This paper presents the testing of several GMPEs selected in current international and national probabilistic projects against weak motions recorded in France (191 recordings with source-site distances up to 300km, 3.8\leqMw\leq4.5). The method is based on the loglikelihood value proposed by Scherbaum et al. (2009). The best fitting models (approximately 2.5\leqLLH\leq3.5) over the whole frequency range are the Cauzzi and Faccioli (2008), Akkar and Bommer (2010) and Abrahamson and Silva (2008) models. No significant regional variation of ground motions is highlighted, and the magnitude scaling could be predominant in the control of ground-motion amplitudes. Furthermore, we take advantage of a rich Japanese dataset to run tests on randomly selected low-magnitude subsets, and check that a dataset of ~190 observations, same size as the French dataset, is large enough to obtain stable LLH estimates. Additionally we perform the tests against larger magnitudes (5-7) from the Japanese dataset. The ranking of models is partially modified, indicating a magnitude scaling effect for some of the models, and showing that extrapolating testing results obtained from low magnitude ranges to higher magnitude ranges is not straightforward

Extraction of bone structure with a single-scan skeletonization driven by distance

International audienceShape description is an important step in image analysis. Skeletonization methods are widely used in image analysis since they are a powerful tool to describe a shape. This paper presents a new single-scan skeletonization using different diskrete distances. The application of this method is the extraction of caracteristics from µCT images in order to estimate the bone state

Path-Based Distance with Varying Weights and Neighborhood Sequences

International audienceThis paper presents a path-based distance where local displacement costs vary both according to the displacement vector and with the travelled distance. The corresponding distance transform algorithm is similar in its form to classical propagation-based algorithms, but the more variable distance increments are either stored in look-up-tables or computed on-the-fly. These distances and distance transform extend neighborhood-sequence distances, chamfer distances and generalized distances based on Minkowski sums. We introduce algorithms to compute, in Z2, a translated version of a neighborhood sequence distance map with a limited number of neighbors, both for periodic and aperiodic sequences. A method to recover the centered distance map from the translated one is also introduced. Overall, the distance transform can be computed with minimal delay, without the need to wait for the whole input image before beginning to provide the result image

Spatio-temporal modeling of avalanche frequencies in the French Alps

AbstractAvalanches threaten mountainous regions, and probabilistic long term hazard evaluation is a useful tool for land use planning and the definition of appropriate mitigation measures. This communication focuses on avalanches counts in the French Alps, and investigates their fluctuations in space and time within a Bayesian hierarchical modeling framework.We have at our disposal a 60 year data set covering the whole French Alps. The considered time scale is the winter. The elementary spatial scale is the township. It is small enough to allow information transfer between neighboring paths and large enough to avoid errors in paths localization. Data are standardized with a variable integrating the number of surveyed paths.A hierarchical Poisson-lognormal model appears well-adapted to depict the observation process with such discrete data. The spatial and temporal effects are assumed independent, and they are considered in the latent layer of the model. The temporal trend is modeled with a cubic spline whereas different spatial dependence sub-models are tested. The latter ones work on different types of supports (continuous field and discrete grid), and at different embedded spatial scales. Model inference and predictive sampling are carried out using Markov Chain Monte Carlo simulation methods. The spatial structure explains the larger part of the relative risks. The spatial dependence is visible at the scale of townships, but with a short range. At the larger scale of the massifs, the spatial dependence is weaker.The regional coherence of the results with the number of avalanche releases suggests that we may also search for other spatially structured variables implicated in the magnitude of avalanches that could help transfer information from one path to another

ANTHRAQUINONE DYESTUFF AND GROWTH OF GALIUM ODORATUM ((L.) SCOP.) RHIZOMES IN RELATION TO ECOPHYSIOLOGICAL AND ONTOGENIC CONDITIONS

Galium odoratum, a member of the Rubiaceae family is known to accumulate anthraquinone dyestuff in the rhizome. The objective of our research was to document ecophysiological variables that modulate the anthraquinone dyestuff content and the growth rate of the underground part of this species. Several variables were taken into consideration : (1) the plant population phenology and the geographic origin of the plant population, for plant material collected in 4 natural stands identified in forests of Belgium, Grand-Duchy of Luxembourg and France, (2) the plant growth conditions, i.e. natural stands vs controlled environment and (3) the plant propagation path, i.e. clonal vs seed propagation. In natural stands, the anthraquinone dyestuff content varied with the plant phenology, being minimal at full flowering stage and the highest at leaf yellowing. It also varied depending on the geographic location of the plant population. Such a difference between plant populations was not observed when plants were grown in controlled environment. Typically, the anthraquinone dyestuff of the plant rhizome was higher in controlled environment than in natural stands, suggesting a strong impact of the growth conditions on anthraquinone biosynthesis. Additionnally, the plant propagation path does not influence the anthraquinone dyestuff content, but when newly formed rhizome was separated into fragments of increasing age –from 27 to 105 days-, a linear increase of the dyestuff with the rhizome ageing was observed

A mutual information-based in vivo monitoring of adaptive response to targeted therapies in melanoma

The mechanisms of adaptive resistance to genetic-based targeted therapies of solid malignancies have been the subject of intense research. These studies hold great promise for finding co-targetable hub/pathways which in turn would control the downstream non-genetic mechanisms of adaptive resistance. Many such mechanisms have been described in the paradigmatic BRAF-mutated melanoma model of adaptive response to BRAF inhibition. Currently, a major challenge for these mechanistic studies is to confirm in vivo, at the single-cell proteomic level, the existence of dependencies between the co-targeted hub/pathways and their downstream effectors. Moreover, the drug-induced in vivo modulation of these dependencies needs to be demonstrated. Here, we implement such single-cell-based in vivo expression dependency quantification using immunohistochemistry (IHC)-based analyses of sequential biopsies in two xenograft models. These mimic phase 2 and 3 trials in our own therapeutic strategy to prevent the adaptive response to BRAF inhibition. In this mechanistic model, the dependencies between the targeted Li2CO3-inducible hub HuR and the resistance effectors are more likely time-shifted and transient since the minority of HuRLow cells, which act as a reservoir of adaptive plasticity, switch to a HuRHigh state as they paradoxically proliferate under BRAF inhibition. Nevertheless, we show that a copula/kernel density estimator (KDE)-based quantification of mutual information (MI) efficiently captures, at the individual level, the dependencies between HuR and two relevant resistance markers pERK and EGFR, and outperforms classic expression correlation coefficients. Ultimately, the validation of MI as a predictive IHC-based metric of response to our therapeutic strategy will be carried in clinical trials.Comment: 9 pages, 5 figures Corrected typo

Inorganic salts effect on wheat straw during steam explosion treatment

Wheat straw is an abundant low cost byproduct. Its use is usually limited in litter and cattle feed. In order to better valorize this lignocellulosic biomass in high added value products, a material preliminary fraction should be done. In this study, a steam explosion pretreatment was applied at different pressure 15 and 20 bar with a residence time of 2 min using different solvents (distilled water and salt water 35g/l NaCl). The objective is to investigate the effect of the operating parameters and salts on the extraction yield of different molecules and their degradation products. The results shows that sodium chloride enhanced the hemicellulose and cellulose removal compared to distilled water

Use of 13C-NMR in structural elucidation of polysaccharides: case of locust bean gum

Locust bean gum (LBG) galactomannans are polysaccharides consisting of a β-(1→4) D-mannopyranosyl backbone substituted to varying degrees in α-(1→6) with single D-galactopyranosyl residues. This basic structure is the same for all galactomannans (Fig. 2). However, when locust bean gum is extracted at different temperatures, the generated fractions exhibit different properties in aqueous solution (viscosity, viscoelasticity, gel formation, thermohydrolysis resistance, etc.). This means that there are differences within the fine structure of the polymers (although the basic structure is the same). Analysis of [13C]-NMR spectra of galactomannans, in combination with other techniques, can provide capital information about fine structural elucidation of the polymers. The method specifies the distribution of lateral galactosyls along the main chain of mannans. Two fractions extracted from locust bean gum at 25 and 80 °C (respectively GM25 and GM80) were comparatively studied by [13C]-NMR. Mannosyls/Galactosyls (M/G) ratios can be determined by considering the intensities of C-1 mannose and galactose signals in [13C]-NMR spectra. This method provides results relatively close to those obtained by GC-MS analysis. Spectra also showed that resonance from C4 of D-mannose residues were split, in evident dependence upon the nearest-neighbor probabilities (“diad frequencies”) of D-galactosyl groups along the mannan chains (Fig. 2). Diad frequencies were obtained by integrating C4(Man) peak areas. F11, F21/F12 and F22 gave respectively the di-, mono- or non-substituted mannose pairs proportions. High percentages of F11 and F22 therefore indicate a more non-homogeneous distribution of lateral galactosyls along the polysaccharide backbone as observed for GM80. The percentages of total lateral substituents obtained by C4(Man) peak analysis [F11 + (F21 or F12)/2] were fairly well correlated with M/G ratios. Splitting of the C-6 substituted D-mannose resonance provides, therefore the basis for determining the next-nearest-neighbor probabilities (triad frequencies) (Fig. 2). However, the spectrum is often not sufficiently resolved to accurately quantify and interpret the results