Significance: Functional near-infrared spectroscopy (fNIRS) has become an important research tool in studying human brains. Accurate quantification of brain activities via fNIRS relies upon solving computational models that simulate the transport of photons through complex anatomy. Aim: We aim to highlight the importance of accurate anatomical modeling in the context of fNIRS and propose a robust method for creating high-quality brain/full-head tetrahedral mesh models for neuroimaging analysis. Approach: We have developed a surface-based brain meshing pipeline that can produce significantly better brain mesh models, compared to conventional meshing techniques. It can convert segmented volumetric brain scans into multilayered surfaces and tetrahedral mesh models, with typical processing times of only a few minutes and broad utilities, such as in Monte Carlo or finite-element-based photon simulations for fNIRS studies. Results: A variety of high-quality brain mesh models have been successfully generated by processing publicly available brain atlases. In addition, we compare three brain anatomical models-the voxel-based brain segmentation, tetrahedral brain mesh, and layered-slab brain model-and demonstrate noticeable discrepancies in brain partial pathlengths when using approximated brain anatomies, ranging between −1.5% to 23% with the voxelated brain and 36% to 166% with the layered-slab brain. Conclusion: The generation and utility of high-quality brain meshes can lead to more accurate brain quantification in fNIRS studies. Our open-source meshing toolboxes "Brain2Mesh" and "Iso2Mesh" are freely available at http://mcx.space/brain2mesh.
Abstract. Glaciers in the Pamir Mountains are generally acknowledged to be
in a stable state and show the least glacial retreat in high-mountain Asia;
however, they are also some of the most dynamic glaciers in the region and
their behaviour has been spatially variable in recent decades. Few data exist
for these glaciers, in particular relating to how they are responding to
recent climatic changes. Here, we utilize Landsat 7 (ETM+), Landsat 8
(OLI), ASTER, and Google Earth optical images acquired between 1999 and 2016
to characterize the dynamics of the glaciers in the Kingata Mountains,
located in the eastern Pamir Mountains. We quantify the velocity, areal, and frontal
changes of these glaciers, which provide us with valuable data on their
recent dynamic evolution and an indication of how they may evolve in future
years. We highlight 28 glaciers among which 17 have changed markedly over the
study period. We identify four advancing glaciers and 13 surge-type glaciers.
The dynamic evolution of the glacier surges shows some similarity with those
of the nearby Karakoram, suggesting that both hydrological and thermal
controls are important for surge initiation and recession. Topography seems
to be a dominant control on non-surge glacier behaviour in the Kingata
Mountains, with the north side of the divide characterized by steep,
avalanche-fed basins and glacier tongues now approaching recession in
contrast to those on the south side of the divide that capture the majority
of precipitation and have much broader plateau-like accumulation zones. This
study is the first synthesis of glacial motion across this region and
provides a baseline with which to compare future changes.
We perform a comparison between the local fractional Adomian decomposition and local fractional function decomposition methods applied to the Laplace equation. The operators are taken in the local sense. The results illustrate the significant features of the two methods which are both very effective and straightforward for solving the differential equations with local fractional derivative.
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