Accepting its random coil nature allows a partial NMR assignment of the neuronal Tau protein

A combined strategy to obtain a partial NMR assignment of the neuronal Tau protein is presented. Confronted with the extreme spectral degeneracy that the spectrum of this 441 amino acid long unstructured protein presents, we have introduced a graphical procedure based on residue type-specific product planes. Combining this strategy with the search for pairwise motifs, and combining the spectra of different Tau isoforms and even of peptides derived from the native sequence, we arrive at a partial assignment that is sufficient to map the interactions of Tau with its molecular partners. The obtained assignments equally confirm the absence of regular secondary structure in the isolated protein.     

Ionic conductivity of amorphous mNaFnMF3 thin films (M=Al,Cr)

Evaporated 0.5 to 0.7 μm thick thin films of mNaFnAlF₃ or mNafnCrF₃ were prepared in a 1 mPa vacuum on glass substrates kept at room temperature. Chemical analysis and AC conductivity measurement revealed that in each case studied, a high ionic conductivity plateau existed for the composition range $\text{0.1 <}\text{n}\text{(m+n)}\text{< 0.4}$. The maximum conductivities at room temperature were σ = 1 × 10^?6 S/mm for NaFAlF₃ and σ = 2 × 10^?5 S/m for NaFCrF₃. Those high conductivities were discussed in terms of arrangement of MF₆ octahedra.     

Computer-aided method for quantification of cartilage thickness and volume changes using MRI: validation study using a synthetic model

The primary objective of this study was to develop a computer-aided method for the quantification of three-dimensional (3-D) cartilage changes over time in knees with osteoarthritis (OA). We introduced a local coordinate system (LCS) for the femoral and tibial cartilage boundaries that provides a standardized representation of cartilage geometry, thickness, and volume. The LCS can be registered in different data sets from the same patient so that results can be directly compared. Cartilage boundaries are segmented from 3-D magnetic resonance (MR) slices with a semi-automated method and transformed into offset-maps, defined by the LCS. Volumes and thickness are computed from these offset-maps. Further anatomical labeling allows focal volumes to be evaluated in predefined subregions. The accuracy of the automated behavior of the method was assessed, without any human intervention, using realistic, synthetic 3-D MR images of a human knee. The error in thickness evaluation is lower than 0.12 mm for the tibia and femur. Cartilage volumes in anatomical subregions show a coefficient of variation ranging from 0.11% to 0.32%. This method improves noninvasive 3-D analysis of cartilage thickness and volume and is well suited for in vivo follow-up clinical studies of OA knees.     

Performance analysis of coated plutonia particle fuel compact for radioisotope heater units

Coated plutonia particle fuel has been proposed recently for use in radioisotope power systems and radioisotope heater units for a variety of space missions requiring power levels from milliwatts to tens or even hundreds of watts. The ²³⁸PuO₂ fuel kernels are coated with a strong layer of ZrC designed to fully retain the helium gas generated by the radioactive decay of ²³⁸Pu. A recent investigation has concluded that helium retention in large-grain (200 μm) granular and polycrystalline fuel kernels is possible even at high-temperatures (>1700 K). Results of performance analysis showed that this fuel form could increase by 2.3–2.4 times the thermal power output of a light weight radioisotope heater unit. These figures are for a single-size (500 μm) particles compact, assuming 10% and 5% helium gas release respectively, and a fuel temperature of 1723 K, following 10 years of storage. A binary-size (300 and 1200 μm) particles compact increases the thermal power output of the RHU by an additional 15%.     

Input addition and leader selection for the controllability of graph-based systems

In this paper, we consider dynamical graph-based models, which are well fitted for the structural analysis of complex systems. A significant amount of work has been devoted to the controllability of such graph based models, e.g. recently for multi-agent systems or complex networks. We study here the controllability through input addition in this framework. We present several variants of this problem depending on the freedom which is left to the designer on the additional inputs. We use a unified framework, which allows us to encompass the different applications and representations (large scale systems, complex communications networks, multi-agent systems, …) and provide convenient graph tools for their analysis. Our contribution is to characterize the structural modifications of the system resulting from an input addition (or a leader selection) and of the mechanisms which lead to controllability. We provide information on the possible location of additional inputs and on the minimal number of inputs to be added for controllability.     

Bibliography on Mathematical Models of Drying and Dryers

Mathematical modelling of drying processes as well as dryers has become an active and challenging area of research internationally. Despite the volume of literature published and continuing to appear on this subject, much remains to be accomplished in view of the intrinsic complexities associated with coupled heat, mass and momentum transfer with or without phase change occurring in porous media which are often deformable as well. Characterization of the solid media is still a major obstacle to modelling of drying. Since industrial drying is increasingly carried out using several modes of heat transfer (e.g. convection coupled wih conduction or microwave or infrared heating modelling of drying or dryers will remain an important research area in the years to come.

We hope that this bibliography will serve as a useful tool for both the novice as well as the experienced researcher in the subject area in locating appropriate literature for a critical evaluation.     

A new tangible user interface for machine learning document review

This paper describes a tool for assisting lawyers and paralegal teams during document review in eDiscovery. The tool combines a machine learning technology (CategoriX) and advanced multi-touch interface capable of not only addressing the usual cost, time and accuracy issues in document review, but also of facilitating the work of the review teams by capitalizing on the intelligence of the reviewers and enabling collaborative work.