Image processing methods for human brain connectivity analysis from in-vivo diffusion MRI

The structural connectivity of the brain is considered to encode species-wise and subject-wise patterns that will unlock large areas of understanding of the human brain. Currently, diffusion MRI of the living brain enables to map the microstructure of tissue, allowing to track the pathways of fiber bundles connecting the cortical regions across the brain. These bundles are summarized in a network representation called connectome that is analyzed using graph theory. The extraction of the connectome from diffusion MRI requires a large processing flow including image enhancement, reconstruction, segmentation, registration, diffusion tracking, etc. Although a concerted effort has been devoted to the definition of standard pipelines for the connectome extraction, it is still crucial to define quality assessment protocols of these workflows. The definition of quality control protocols is hindered by the complexity of the pipelines under test and the absolute lack of gold-standards for diffusion MRI data. Here we characterize the impact on structural connectivity workflows of the geometrical deformation typically shown by diffusion MRI data due to the inhomogeneity of magnetic susceptibility across the imaged object. We propose an evaluation framework to compare the existing methodologies to correct for these artifacts including whole-brain realistic phantoms. Additionally, we design and implement an image segmentation and registration method to avoid performing the correction task and to enable processing in the native space of diffusion data. We release PySDCev, an evaluation framework for the quality control of connectivity pipelines, specialized in the study of susceptibility-derived distortions. In this context, we propose Diffantom, a whole-brain phantom that provides a solution to the lack of gold-standard data. The three correction methodologies under comparison performed reasonably, and it is difficult to determine which method is more advisable. We demonstrate that susceptibility-derived correction is necessary to increase the sensitivity of connectivity pipelines, at the cost of specificity. Finally, with the registration and segmentation tool called regseg we demonstrate how the problem of susceptibility-derived distortion can be overcome allowing data to be used in their original coordinates. This is crucial to increase the sensitivity of the whole pipeline without any loss in specificity.

Analysis of SnS2 hyperdoped with V proposed as efficient absorber material

Intermediate-band materials can improve the photovoltaic efficiency of solar cells through the absorption of two subband-gap photons that allow extra electron-hole pair formations. Previous theoretical and experimental findings support the proposal that the layered SnS2 compound, with a band-gap of around 2 eV, is a candidate for an intermediate-band material when it is doped with a specific transition-metal. In this work we characterize vanadium doped SnS2 using density functional theory at the dilution level experimentally found and including a dispersion correction combined with the site-occupancy-disorder method. In order to analyze the electronic characteristics that depend on geometry, two SnS2 polytypes partially substituted with vanadium in symmetry-adapted non-equivalent configurations were studied. In addition the magnetic configurations of vanadium in a SnS2 2H-polytype and its comparison with a 4H-polytype were also characterized. We demonstrate that a narrow intermediate-band is formed, when these dopant atoms are located in different layers. Our theoretical predictions confirm the recent experimental findings in which a paramagnetic intermediate-band material in a SnS2 2H-polytype with 10% vanadium concentration is obtained.

Magnetic disorder in TbAl2 nanoparticles

The magnetic and thermal properties of TbAl2 nanosized alloys (diameters, 12 nm $\leqslant D\leqslant $ 20 nm) obtained by high-energy milling are characterised by specific heat, magnetisation and neutron scattering. The specific heat shows that the λ-anomaly at Curie temperature vanishes when the milling time reaches 300 h and its field variation shows a broad peak around 70 K disclosing a disordered magnetic state. The thermal variation of magnetization follows a Bloch process with a decrease of the stiffness constant and a faster demagnetisation with a quadratic exponent instead of the bulk ordinary ${T}^{3/2}$-dependence. The magnetic moment reduction in the nanosized alloys follows a 1/D dependence, remarking the role of disordered moment surface. The Rietveld analysis of the neutron diffraction patterns indicates a collinear ferromagnetic structure, with a reduction of the Tb-magnetic moment when decreasing the particle size. The temperature dependent overall magnetic signal of nanoparticles is derived from small-angle neutron scattering. A magnetic nanoparticle structure with an ordered ferromagnetic core and a disordered surface layer is proposed.