Characterization and modeling of diffusion process for mass transport through the Tournemire argillites (Aveyron, France)

Argillites are one of the geological formations studied by IRSN for their confining properties for isolation of radioactive wastes. One of the main objectives is the study of water transport through rocks with very low water content and very low hydraulic conductivity by modeling of natural tracer profiles. This paper presents the protocol developed for and applied to the acquisition of data for chloride content in interstitial water of the Toarcian argillites at the Tournemire site (Southern France). This protocol is based on laboratory diffusion experiments and on modeling. Experimental data obtained during the transient and steady-state parts of diffusion experiments enable, respectively, the assessment of the diffusion coefficient and the determination of Cl concentration in pore water. Using this protocol, profiles with depth for both of these data sets have been acquired along the geological sequence. Taking into account the present knowledge of the geological and hydrogeological history of the Tournemire massif, a conceptual model granting the main role for mass transport to diffusion has been proposed. According to this conceptual model, a one-dimensional numerical model was built for simulating the mass transport of chloride through the sedimentary column, over 53 Ma. The good agreement between experimental data and calculated values for both diffusion coefficients and concentrations of chloride confirms that diffusion is likely the main process for mass transport in the massif. This model was also tested with the deuterium content of interstitial water, applying variable concentrations at the aquifer system boundaries for reflecting the thermal dependency of isotopic composition in precipitation. These simulations also reveal the likely important role of heterogeneities, such as fractures, in the variability of tracer concentrations with regards to a simple diffusion profile.     

Linking the proteins--elucidation of proteome-scale networks using mass spectrometry

Proteomes are intricate. Typically, thousands of proteins interact through physical association and post-translational modifications (PTMs) to give rise to the emergent functions of cells. Understanding these functions requires one to study proteomes as "systems" rather than collections of individual protein molecules. The abstraction of the interacting proteome to "protein networks" has recently gained much attention, as networks are effective representations, that lose specific molecular details, but provide the ability to see the proteome as a whole. Mostly two aspects of the proteome have been represented by network models: proteome-wide physical protein-protein-binding interactions organized into Protein Interaction Networks (PINs), and proteome-wide PTM relations organized into Protein Signaling Networks (PSNs). Mass spectrometry (MS) techniques have been shown to be essential to reveal both of these aspects on a proteome-wide scale. Techniques such as affinity purification followed by MS have been used to elucidate protein-protein interactions, and MS-based quantitative phosphoproteomics is critical to understand the structure and dynamics of signaling through the proteome. We here review the current state-of-the-art MS-based analytical pipelines for the purpose to characterize proteome-scale networks.     

Localization-limited exciton oscillator strength in colloidal CdSe nanoplatelets revealed by the optically induced stark effect

2D materials are considered for applications that require strong light-matter interaction because of the apparently giant oscillator strength of the exciton tra...     

Cytocompatibility of titanium metal injection molding with various anodic oxidation post-treatments

Metal injection molding (MIM) is a near net shape manufacturing method that allows for the production of components of small to moderate size and complex shape. MIM is a cost-effective and flexible manufacturing technique that provides a large innovative potential over existing methods for the industry of implantable devices. Commercially pure titanium (CP-Ti) samples were machined to the same shape as a composite feedstock with titanium and polyoxymethylene, and these metals were injected, debinded and sintered to assess comparative biological properties. Moreover, we treated MIM-Ti parts with BIOCOAT®, BIODIZE® and BIOCER®, three different anodic oxidation techniques that treat titanium using acid, alkaline and anion enriched electrolytes, respectively. Cytocompatibility as well as morphological and chemical features of surfaces was comparatively assessed on each sample, and the results revealed that MIM-Ti compared to CP-Ti demonstrated a specific surface topography with a higher roughness. MIM-Ti and BIOCER® samples significantly enhanced cell proliferation, cell adhesion and cell differentiation compared to CP-Ti. Interestingly, in the anodization post-treatment established in this study, we demonstrated the ability to improve osseointegration through anionic modification treatment. The excellent biological response we observed with MIM parts using the injection molding process represents a promising manufacturing method for the future implantable devices in direct contact with bones.     

Adaptive trajectory tracking despite unknown input delay and plant parameters

In a recent paper we presented the first adaptive control design for an ODE system with a possibly large actuator delay of unknown length. We achieved global stability under full state feedback. In this paper we generalize the design to the situation where, besides the unknown delay value, the ODE also has unknown parameters, and where trajectory tracking (rather than equilibrium regulation) is pursued.     

Mining the Wheat Grain Proteome

Bread wheat is the most widely cultivated crop worldwide, used in the production of food products and a feed source for animals. Selection tools that can be applied early in the breeding cycle are needed to accelerate genetic gain for increased wheat production while maintaining or improving grain quality if demand from human population growth is to be fulfilled. Proteomics screening assays of wheat flour can assist breeders to select the best performing breeding lines and discard the worst lines. In this study, we optimised a robust LC–MS shotgun quantitative proteomics method to screen thousands of wheat genotypes. Using 6 cultivars and 4 replicates, we tested 3 resuspension ratios (50, 25, and 17 µL/mg), 2 extraction buffers (with urea or guanidine-hydrochloride), 3 sets of proteases (chymotrypsin, Glu-C, and trypsin/Lys-C), and multiple LC settings. Protein identifications by LC–MS/MS were used to select the best parameters. A total 8738 wheat proteins were identified. The best method was validated on an independent set of 96 cultivars and peptides quantities were normalised using sample weights, an internal standard, and quality controls. Data mining tools found particularly useful to explore the flour proteome are presented (UniProt Retrieve/ID mapping tool, KEGG, AgriGO, REVIGO, and Pathway Tools).     

Airfoil optimisation for vertical‐axis wind turbines with variable pitch

To advance the design of a multimegawatt vertical‐axis wind turbine (VAWT), application‐specific airfoils need to be developed. In this research, airfoils are tailored for a VAWT with variable pitch. A genetic algorithm is used to optimise the airfoil shape considering a balance between the aerodynamic and structural performance of airfoils. At rotor scale, the aerodynamic objective aims to create the required optimal loading while minimising losses. The structural objective focusses on maximising the bending stiffness. Three airfoils from the Pareto front are selected and analysed using the actuator cylinder model and a prescribed‐wake vortex code. The optimal pitch schedule is determined, and the loadings and power performance are studied for different tip‐speed ratios and solidities. The comparison of the optimised airfoils with similar airfoils from the first generation shows a significant improvement in performance, and this proves the necessity to properly select the airfoil shape.     

Identification of ritual blood in African artifacts using TOF-SIMS and synchrotron radiation microspectroscopies

A new protocol is implemented to demonstrate the presence of blood in the patina of African art objects from Mali. Divided into three steps, the protocol first consists in demonstrating the presence of proteins and localizing them in the sample's cross sections using time-of-flight secondary ion mass spectrometry (TOF-SIMS) and synchrotron-based infrared microspectrometry (microFT-IR). In a second time, TOF-SIMS is used to investigate heme, which is a blood marker. If heme is missing, which could mean that it is too degraded to be detected, X-ray microfluorescence (microXRF) and X-ray absorption near-edge microspectroscopy (microXANES) are used to prove the presence of iron in the protein area and to get a fingerprint of its chemical environment. This permits us thus to demonstrate that iron is indeed linked with proteins and not with mineral phases of the sample. Coupled with the ritual context of the objects, this constitutes a proof of the use of blood. Thanks to this protocol, which has the major advantage of avoiding false positive results, the presence of blood has been demonstrated in seven out of the eight studied samples.     

Mixture distribution latent state-trait analysis: Basic ideas and applications.

Extensions of latent state-trait models for continuous observed variables to mixture latent state-trait models with and without covariates of change are presented that can separate individuals differing in their occasion-specific variability. An empirical application to the repeated measurement of mood states (N = 501) revealed that a model with 2 latent classes fits the data well. The larger class (76%) consists of individuals whose mood is highly variable, whose general well-being is comparatively lower, and whose mood variability is influenced by daily hassles and uplifts. The smaller class (24%) represents individuals who are rather stable and happier and whose mood is influenced only by daily uplifts but not by daily hassles. A simulation study on the model without covariates with 5 sets of sample sizes and 5 sets of number of occasions revealed that the appropriateness of the parameter estimates of this model depends on number of observations (the higher the better) and number of occasions (the higher the better). Another simulation study estimated Type I and II errors of the Lo-Mendell-Rubin test. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

The time course of spoken word learning and recognition: Studies with artificial lexicons.

The time course of spoken word recognition depends largely on the frequencies of a word and its competitors, or neighbors (similar-sounding words). However, variability in natural lexicons makes systematic analysis of frequency and neighbor similarity difficult. Artificial lexicons were used to achieve precise control over word frequency and phonological similarity. Eye tracking provided time course measures of lexical activation and competition (during spoken instructions to perform visually guided tasks) both during and after word learning, as a function of word frequency, neighbor type, and neighbor frequency. Apparent shifts from holistic to incremental competitor effects were observed in adults and neural network simulations, suggesting such shifts reflect general properties of learning rather than changes in the nature of lexical representations. (PsycINFO Database Record (c) 2010 APA, all rights reserved)