A new method to derive white matter conductivity from diffusion tensor MRI

We propose a new algorithm to derive the anisotropic conductivity of the cerebral white matter (WM) from the diffusion tensor MRI (DT-MRI) data. The transportation processes for both water molecules and electrical charges are described through a common multicompartment model that consists of axons, glia, or the cerebrospinal fluid (CSF). The volume fraction (VF) of each compartment varies from voxel to voxel and is estimated from the measured diffusion tensor. The conductivity tensor at each voxel is then computed from the estimated VF values and the decomposed eigenvectors of the diffusion tensor. The proposed VF algorithm was applied to the DT-MRI data acquired from two healthy human subjects. The extracted anisotropic conductivity distribution was compared with those obtained by using two existing algorithms, which were based upon a linear conductivity-to-diffusivity relationship and a volume constraint, respectively. The present results suggest that the VF algorithm is capable of incorporating the partial volume effects of the CSF and the intravoxel fiber crossing structure, both of which are not addressed altogether by existing algorithms. Therefore, it holds potential to provide a more accurate estimate of the WM anisotropic conductivity, and may have important applications to neuroscience research or clinical applications in neurology and neurophysiology.      

Numerically accurate computational techniques for optimal estimator analyses of multi-parameter models

Modelling unclosed terms in partial differential equations typically involves two steps: First, a set of known quantities needs to be specified as input parameters for a model, and second, a specific functional form needs to be defined to model the unclosed terms by the input parameters. Both steps involve a certain modelling error, with the former known as the irreducible error and the latter referred to as the functional error. Typically, only the total modelling error, which is the sum of functional and irreducible error, is assessed, but the concept of the optimal estimator enables the separate analysis of the total and the irreducible errors, yielding a systematic modelling error decomposition. In this work, attention is paid to the techniques themselves required for the practical computation of irreducible errors. Typically, histograms are used for optimal estimator analyses, but this technique is found to add a non-negligible spurious contribution to the irreducible error if models with multiple input parameters are assessed. Thus, the error decomposition of an optimal estimator analysis becomes inaccurate, and misleading conclusions concerning modelling errors may be drawn. In this work, numerically accurate techniques for optimal estimator analyses are identified and a suitable evaluation of irreducible errors is presented. Four different computational techniques are considered: a histogram technique, artificial neural networks, multivariate adaptive regression splines, and an additive model based on a kernel method. For multiple input parameter models, only artificial neural networks and multivariate adaptive regression splines are found to yield satisfactorily accurate results. Beyond a certain number of input parameters, the assessment of models in an optimal estimator analysis even becomes practically infeasible if histograms are used. The optimal estimator analysis in this paper is applied to modelling the filtered soot intermittency in large eddy simulations using a dataset of a direct numerical simulation of a non-premixed sooting turbulent flame.     

A lattice test of strong coupling behaviour in QCD at finite temperature

We propose a set of lattice measurements which could test whether the deconfined, quark–gluon plasma, phase of QCD shows strong coupling aspects at temperatures a few times the critical temperature for deconfinement. The measurements refer to twist-two operators which are not protected by symmetries and which in a strong-coupling scenario would develop large, negative, anomalous dimensions, resulting in a strong suppression of the respective lattice expectation values in the continuum limit. Special emphasis is put on the twist-two operator with lowest spin (the spin-2 operator orthogonal to the energy–momentum tensor within the renormalization flow) and on the case of quenched QCD, where this operator is known for arbitrary values of the coupling: this is the quark energy–momentum tensor. The proposed lattice measurements could also test whether the plasma constituents are pointlike (as expected at weak coupling), or not.     

MXCuBE3: A New Era of MX-Beamline Control Begins

The outstanding success of structural biology within the last two decades is closely related to the development and evolution of macromolecular crystallography (MX) beamlines. Indeed, many of today's synchrotron-based MX experimental sessions aim for fast but rigorous evaluations and data collections from very large numbers of samples [1 A. Joachimiak, Current Opinion in Structural Biology 19, 573–584 (2009).[Crossref], [PubMed], [Web of Science ®] , [Google Scholar]–7 R. L. Owen, Archives of Biochemistry and Biophysics 602, 21–31 (2016).[Crossref], [PubMed], [Web of Science ®] , [Google Scholar]]. To facilitate this, sample changing on most MX beamlines is now carried out by robots and the centering of a crystal in the X-ray beam to micrometer precision is now automatically performed using either optical or diffraction-based techniques [8 D. Nurizzo, Acta Cryst. D 72, 966–975 (2016).[Crossref] , [Google Scholar]]. Once a crystal is centered, users have a wide array of options at their disposal to prepare any given experiment. This includes: X-ray fluorescence (XRF) [9 G. A. Leonard, Journal of Applied Crystallography 42, 333–335 (2009).[Crossref], [Web of Science ®] , [Google Scholar]] analysis to confirm the presence of anomalous scatterers in crystals; X-ray absorption near-edge scans (XANES) to determine the best X-ray wavelengths for MAD/SAD data collection [10 W. A. Hendrickson, Methods Enzymol. 276, 494–523 (1997).[Crossref], [PubMed], [Web of Science ®] , [Google Scholar]]; and the probing of the diffraction properties of crystals to determine the best crystal, or area of a crystal [11 M. W. Bowler, Acta Cryst. D 66, 855–864 (2010).[Crossref], [PubMed], [Web of Science ®] , [Google Scholar]], for data collection. All of these operations are now also automated, as is the collection of the final diffraction data set either from single or multiple crystals and the subsequent data analysis and reduction.     

On two-phase flow patterns and transition criteria in aqueous methanol and CO2 mixtures in adiabatic,rectangular microchannels

This paper presents flow map investigations of adiabatic two-phase flow in square cross-sectioned, 200 μm deep microchannels fabricated in silicon, employing laser induced fluorescence microscopy. The influence of surface tension and nozzle geometry on the flow pattern transition was investigated using two nozzle widths (orifices of 30 μm and 50 μm, respectively) and methanol–water solutions with CO₂ as the gas phase. It was found and quantified that smaller nozzle geometries and smaller liquid surface tension promote the propagation of capillary gas bubbles at lower superficial gas and liquid velocities. Within the measurement domain of superficial gas (0.01–0.625 m/s) and liquid (0.0005–0.5000 m/s) velocities, we observed dispersed bubbly, regularly ordered bubbly, wedging, slug and annular flows, thus extending the experimental knowledge base to smaller superficial liquid velocities by almost two orders of magnitude. With the help of the flow maps presented herein, we were able to characterize the observed regularly ordered bubbly flow as the transition regime between dispersed bubbly and wedging flow. The results of the present investigation are of direct relevance to the operation of small-scale direct methanol fuel cells.     

Analyser‐based tomography images of cartilage

Analyser‐based imaging expands the performance of X‐ray imaging by utilizing not only the absorption properties of X‐rays but also the refraction and scatter rejection (extinction) properties. In this study, analyser‐based computed tomography has been implemented on imaging an articular cartilage sample, depicting substructural variations, without overlay, at a pixel resolution of 3.6 µm.     

Mechanism by which Tungsten Oxide Promotes the Activity of Supported V2O5/TiO2 Catalysts for NOX Abatement: Structural Effects Revealed by 51V MAS NMR Spectroscopy

The selective catalytic reduction (SCR) of NO_x with NH₃ to N₂ with supported V₂O₅(‐WO₃)/TiO₂ catalysts is an industrial technology used to mitigate toxic emissions. Long‐standing uncertainties in the molecular structures of surface vanadia are clarified, whereby progressive addition of vanadia to TiO₂ forms oligomeric vanadia structures and reveals a proportional relationship of SCR reaction rate to [surface VO_x concentration]², implying a 2‐site mechanism. Unreactive surface tungsta (WO₃) also promote the formation of oligomeric vanadia (V₂O₅) sites, showing that promoter incorporation enhances the SCR reaction by a structural effect generating adjacent surface sites and not from electronic effects as previously proposed. The findings outline a method to assess structural effects of promoter incorporation on catalysts and reveal both the dual‐site requirement for the SCR reaction and the important structural promotional effect that tungsten oxide offers for the SCR reaction by V₂O₅/TiO₂ catalysts.