Towards a global criteria based framework for the sustainability assessment of bioethanol supply chains: application to the Swiss dilemma : is local produced bioethanol more sustainable than bioethanol imported from Brazil?

Biofuels are considered as a promising substitute for fossil fuels when considering the possible reduction of greenhouse gases emissions. However limiting their impacts on potential benefits for reducing climate change is shortsighted. Global sustainability assessments are necessary to determine the sustainability of supply chains. We propose a new global criterion based framework enabling a comprehensive international comparison of bioethanol supply chains. The interest of this framework is that the selection of the sustainability indicators is qualified on three criterions: relevance, reliability and adaptability to the local context. Sustainability issues have been handled along environmental, social and economical issues. This new framework has been applied for a specific issue: from a Swiss perspective, is locally produced bioethanol in Switzerland more sustainable than imported from Brazil? Thanks to this framework integrating local context in its indicator definition, Brazilian production of bioethanol is shown as energy efficient and economically interesting for Brazil. From a strictly economic point of view, bioethanol production within Switzerland is not justified for Swiss consumption and questionable for the environmental issue. The social dimension is delicate to assess due to the lack of reliable data and is strongly linked to the agricultural policy in both countries. There is a need of establishing minimum sustainability criteria for imported bioethanol to avoid unwanted negative or leakage effects.

Inflammation And Autoimmune Responses Are Independent Of Peripheral Mhc Class Ii Expression Driven By Ciita Piv In Collagen Induced Arthritis

Background In rheumatoid arthritis (RA), non-professional antigen presenting cells (APCs) such as fi broblast-like synoviocytes (FLS) can express MHC class II (MHCII) molecules and function as non-professional APCs in vitro.Objective To examine the regulation of MHCII expression in FLS and to investigate the role of FLS as non-professional APCs in collagen-induced arthritis (CIA). Methods Expression of MHCII, CIITA and Ciita isoforms pI, pIII and pIV was examined by RT-qPCR, immunohistochemistry and fl ow cytometry in human synovial tissues, arthritic mouse joints and human as well as mouse FLS. CIA was induced in mice knockout for the isoform IV of Ciita (pIV-/-), in pIV-/- mice transgenic for CIITA in the thymus (pIV-/- K14 CIITA) and in control littermates in the DBA/1 background by immunising with bovine collagen type II (CII) in complete Freund's adjuvant.Results HLA-DRA, total CIITA and CIITA pIII mRNA levels were signifi cantly increased in the synovial tissues from RA compared to osteoarthritis patients. Human FLS expressed surface MHCII via CIITA pIII and pIV, while MHCII expression in murine FLS was entirely mediated by pIV. pIV-/- mice lacked both inducible MHCII expression on non-professional APCs including FLS, and in the thymic cortex. The thymic defect in pIV-/- mice impaired CD4+ positive selection, thus protecting pIV-/- mice from CIA by preventing CD4+ T cells immune responses against CII and blocking the release of IFN-γ and IL-17 in ex vivo stimulated lymph node cells. The production of T dependent, arthritogenic anti-CII antibodies was also impaired in pIV-/- mice. A normal thymic expression of MHCII and CD4+ T cell repertoire was obtained in pIV-/- K14 CIITA Tg mice. Immune responses against CII were restored in pIV-/- K14 CIITA Tg mice, as well as the arthritis incidence and clinical severity despite the lack of MHCII expression by mouse FLS. At histology, infl ammation andneutrophils infi ltration scores were not reduced in pIV-/- K14 CIITA Tg mice, while the bone erosion score was signifi cantly lower than in controls.Conclusion Over expression of MHCII is tightly correlated with CIITA pIII in the arthritic human synovium. MHCII is induced via CIITA pIII and pIV in human FLS. In the mouse, MHCII expression in the thymic cortex and in FLS is strictly dependent upon Ciita pIV. The lack of Ciita pIV in the periphery of pIV-/- K14 CIITA Tg mice lowered the bone erosion score but did not signifi cantly protect from infl ammation and autoimmune responses in CIA.

A framework to understand the variations of PSD-95 expression in brain aging and in Alzheimer's disease.

The postsynaptic density protein PSD-95 is a major element of synapses. PSD-95 is involved in aging, Alzheimer's disease (AD) and numerous psychiatric disorders. However, contradictory data about PSD-95 expression in aging and AD have been reported. Indeed in AD versus control brains PSD-95 varies according to regions, increasing in the frontal cortex, at least in a primary stage, and decreasing in the temporal cortex. In contrast, in transgenic mouse models of aging and AD PSD-95 expression is decreased, in behaviorally aged impaired versus unimpaired rodents it can decrease or increase and finally, it is increased in rodents grown in enriched environments. Different factors explain these contradictory results in both animals and humans, among others concomitant psychiatric endophenotypes, such as depression. The possible involvement of PSD-95 in reactive and/or compensatory mechanisms during AD progression is underscored, at least before the occurrence of important synaptic elimination. Thus, in AD but not in AD transgenic mice, enhanced expression might precede the diminution commonly observed in advanced aging. A two-compartments cell model, separating events taking place in cell bodies and synapses, is presented. Overall these data suggest that AD research will progress by untangling pathological from protective events, a prerequisite for effective therapeutic strategies.

A coherent neurobiological framework for functional neuroimaging provided by a model integrating compartmentalized energy metabolism.

Functional neuroimaging has undergone spectacular developments in recent years. Paradoxically, its neurobiological bases have remained elusive, resulting in an intense debate around the cellular mechanisms taking place upon activation that could contribute to the signals measured. Taking advantage of a modeling approach, we propose here a coherent neurobiological framework that not only explains several in vitro and in vivo observations but also provides a physiological basis to interpret imaging signals. First, based on a model of compartmentalized energy metabolism, we show that complex kinetics of NADH changes observed in vitro can be accounted for by distinct metabolic responses in two cell populations reminiscent of neurons and astrocytes. Second, extended application of the model to an in vivo situation allowed us to reproduce the evolution of intraparenchymal oxygen levels upon activation as measured experimentally without substantially altering the initial parameter values. Finally, applying the same model to functional neuroimaging in humans, we were able to determine that the early negative component of the blood oxygenation level-dependent response recorded with functional MRI, known as the initial dip, critically depends on the oxidative response of neurons, whereas the late aspects of the signal correspond to a combination of responses from cell types with two distinct metabolic profiles that could be neurons and astrocytes. In summary, our results, obtained with such a modeling approach, support the concept that both neuronal and glial metabolic responses form essential components of neuroimaging signals.

On-line event detection by recursive dynamic principal component analysis and gas sensor arrays under drift conditions

Leakage detection is an important issue in many chemical sensing applications. Leakage detection hy thresholds suffers from important drawbacks when sensors have serious drifts or they are affected by cross-sensitivities. Here we present an adaptive method based in a Dynamic Principal Component Analysis that models the relationships between the sensors in the may. In normal conditions a certain variance distribution characterizes sensor signals. However, in the presence of a new source of variance the PCA decomposition changes drastically. In order to prevent the influence of sensor drifts the model is adaptive and it is calculated in a recursive manner with minimum computational effort. The behavior of this technique is studied with synthetic signals and with real signals arising by oil vapor leakages in an air compressor. Results clearly demonstrate the efficiency of the proposed method.

Two-stage prograde and retrograde Variscan metamorphism of glaucophane-eclogites, blueschists and greenschists from Ile de Groix (Brittany, France)

On Ile de Groix, Variscan metamorphic former tholeiitic and alkaline basalts occur as glaucophane-eclogites, blueschists and greenschists in isolated lenses and layers within metapelites. Whole-rock delta O-18(SMOW) values of the metabasites show limited variations (10.4-12.0 parts per thousand) and no systematic differences among rock types and metamorphic grades. This provides no argument for large-scale blueschist-to-greenschist transformation driven by infiltration of externally derived fluids. Metamorphic mineralogical changes should have been triggered by internal fluids. Element variations in interlayered blue- and greenschists can be attributed to magmatic fractionation. Assemblages with garnet, clinopyroxene and glaucophane of a high-pressure/low-temperature (HP-LT) metamorphism M1, and NaCa-amphiboles (barroisite, magnesiohornblende, actinolite) of a medium-pressure/medium-temperature metamorphism M2 crystallized during deformation Dl. Detailed core-rim zonation profiles display increasing and then decreasing Al-IV in glaucophane of M1. NaCa-amphiboles of M2, mantling glaucophane and crystallized in porphyroblasts, show first increasing, then decreasing, Al-IV and Al-IV. Empirically calibrated thermobarometers allowed P-T path reconstructions. In glaucophane-eclogites of a metamorphic zone I, a prograde evolution to M1 peak conditions at 400-500 degreesC/10-12 kbar was followed by a retrograde P-T path within the glaucophane stability field. The subsequent M2 evolution was again prograde up to > 600 degreesC at 8 kbar and then retrograde. Similarly, in metamorphic zones II and III, prograde and retrograde paths of MI and M2 at lower maximal temperatures and pressures exist. The almost complete metamorphic cycle during M2 signalizes that the HP-LT rocks escaped from an early erosion by a moderate second burial event and explains the longlasting slow uplift with low average cooling rates.

Domain Adaptation in remote sensing: increasing the portability of land-cover classifiers

Among the types of remote sensing acquisitions, optical images are certainly one of the most widely relied upon data sources for Earth observation. They provide detailed measurements of the electromagnetic radiation reflected or emitted by each pixel in the scene. Through a process termed supervised land-cover classification, this allows to automatically yet accurately distinguish objects at the surface of our planet. In this respect, when producing a land-cover map of the surveyed area, the availability of training examples representative of each thematic class is crucial for the success of the classification procedure. However, in real applications, due to several constraints on the sample collection process, labeled pixels are usually scarce. When analyzing an image for which those key samples are unavailable, a viable solution consists in resorting to the ground truth data of other previously acquired images. This option is attractive but several factors such as atmospheric, ground and acquisition conditions can cause radiometric differences between the images, hindering therefore the transfer of knowledge from one image to another. The goal of this Thesis is to supply remote sensing image analysts with suitable processing techniques to ensure a robust portability of the classification models across different images. The ultimate purpose is to map the land-cover classes over large spatial and temporal extents with minimal ground information. To overcome, or simply quantify, the observed shifts in the statistical distribution of the spectra of the materials, we study four approaches issued from the field of machine learning. First, we propose a strategy to intelligently sample the image of interest to collect the labels only in correspondence of the most useful pixels. This iterative routine is based on a constant evaluation of the pertinence to the new image of the initial training data actually belonging to a different image. Second, an approach to reduce the radiometric differences among the images by projecting the respective pixels in a common new data space is presented. We analyze a kernel-based feature extraction framework suited for such problems, showing that, after this relative normalization, the cross-image generalization abilities of a classifier are highly increased. Third, we test a new data-driven measure of distance between probability distributions to assess the distortions caused by differences in the acquisition geometry affecting series of multi-angle images. Also, we gauge the portability of classification models through the sequences. In both exercises, the efficacy of classic physically- and statistically-based normalization methods is discussed. Finally, we explore a new family of approaches based on sparse representations of the samples to reciprocally convert the data space of two images. The projection function bridging the images allows a synthesis of new pixels with more similar characteristics ultimately facilitating the land-cover mapping across images.

Building a Social Accounting Matrix within the ESA95 Framework: Obtaining a Dataset for Applied General Equilibrium Modelling

This research provides a description of the process followed in order to assemble a "Social Accounting Matrix" for Spain corresponding to the year 2000 (SAMSP00). As argued in the paper, this process attempts to reconcile ESA95 conventions with requirements of applied general equilibrium modelling. Particularly, problems related to the level of aggregation of net taxation data, and to the valuation system used for expressing the monetary value of input-output transactions have deserved special attention. Since the adoption of ESA95 conventions, input-output transactions have been preferably valued at basic prices, which impose additional difficulties on modellers interested in computing applied general equilibrium models. This paper addresses these difficulties by developing a procedure that allows SAM-builders to change the valuation system of input-output transactions conveniently. In addition, this procedure produces new data related to net taxation information.