Focusing and alignment of erythrocytes in a viscoelastic medium

118Ysciescopu

In-vivo data-driven parcellation of Heschl’s gyrus using structural connectivity

The human auditory cortex around Heschl’s gyrus (HG) exhibits diverging patterns across individuals owing to the heterogeneity of its substructures. In this study, we investigated the subregions of the human auditory cortex using data-driven machine-learning techniques at the individual level and assessed their structural and functional profiles. We studied an openly accessible large dataset of the Human Connectome Project and identified the subregions of the HG in humans using data-driven clustering techniques with individually calculated imaging features of cortical folding and structural connectivity information obtained via diffusion magnetic resonance imaging tractography. We characterized the structural and functional profiles of each HG subregion according to the cortical morphology, microstructure, and functional connectivity at rest. We found three subregions. The first subregion (HG1) occupied the central portion of HG, the second subregion (HG2) occupied the medial-posterior-superior part of HG, and the third subregion (HG3) occupied the lateral-anterior-inferior part of HG. The HG3 exhibited strong structural and functional connectivity to the association and paralimbic areas, and the HG1 exhibited a higher myelin density and larger cortical thickness than other subregions. A functional gradient analysis revealed a gradual axis expanding from the HG2 to the HG3. Our findings clarify the individually varying structural and functional organization of human HG subregions and provide insights into the substructures of the human auditory cortex

Hybrid bright-field and hologram imaging of cell dynamics

Volumetric observation is essential for understanding the details of complex biological phenomena. In this study, a bright-field microscope, which provides information on a specific 2D plane, and a holographic microscope, which provides information spread over 3D volumes, are integrated to acquire two complementary images simultaneously. The developed system was successfully applied to capture distinct T-cell adhesion dynamics on inflamed endothelial layers, including capture, rolling, crawling, transendothelial migration, and subendothelial migration.113Ysciescopu

The orbitofrontal cortex functionally links obesity and white matter hyperintensities

© 2020, The Author(s).Many studies have linked dysfunction in cognitive control-related brain regions with obesity and the burden of white matter hyperintensities (WMHs). This study aimed to explore how functional connectivity differences in the brain are associated with WMH burden and degree of obesity using resting-state functional magnetic resonance imaging (fMRI) in 182 participants. Functional connectivity measures were compared among four different groups: (1) low WMH burden, non-obese; (2) low WMH burden, obese; (3) high WMH burden, non-obese; and (4) high WMH burden, obese. At a large-scale network-level, no networks showed significant interaction effects, but the frontoparietal network showed a main effect of degree of obesity. At a finer node level, the orbitofrontal cortex showed interaction effects between periventricular WMH burden and degree of obesity. Higher functional connectivity was observed when the periventricular WMH burden and degree of obesity were both high. These results indicate that the functional connectivity of the orbitofrontal cortex is affected by the mutual interaction between the periventricular WMHs and degree of obesity. Our results suggest that this region links obesity with WMHs in terms of functional connectivity11sciescopu

Convolutional State Space Models for Long-Range Spatiotemporal Modeling

Effectively modeling long spatiotemporal sequences is challenging due to the need to model complex spatial correlations and long-range temporal dependencies simultaneously. ConvLSTMs attempt to address this by updating tensor-valued states with recurrent neural networks, but their sequential computation makes them slow to train. In contrast, Transformers can process an entire spatiotemporal sequence, compressed into tokens, in parallel. However, the cost of attention scales quadratically in length, limiting their scalability to longer sequences. Here, we address the challenges of prior methods and introduce convolutional state space models (ConvSSM) that combine the tensor modeling ideas of ConvLSTM with the long sequence modeling approaches of state space methods such as S4 and S5. First, we demonstrate how parallel scans can be applied to convolutional recurrences to achieve subquadratic parallelization and fast autoregressive generation. We then establish an equivalence between the dynamics of ConvSSMs and SSMs, which motivates parameterization and initialization strategies for modeling long-range dependencies. The result is ConvS5, an efficient ConvSSM variant for long-range spatiotemporal modeling. ConvS5 significantly outperforms Transformers and ConvLSTM on a long horizon Moving-MNIST experiment while training 3X faster than ConvLSTM and generating samples 400X faster than Transformers. In addition, ConvS5 matches or exceeds the performance of state-of-the-art methods on challenging DMLab, Minecraft and Habitat prediction benchmarks and enables new directions for modeling long spatiotemporal sequences

The Non-Destructive and Nano-Microstructural Characterization of Thermal-Barrier Coatings

The durability of thermal barrier coatings (TBCs) plays an important role in the service reliability and maintainability of hot-section components in advanced turbine engines for aerospace and utility applications. Photostimulated luminescence spectroscopy (PSLS) and electrochemical impedance spectroscopy (EIS) are being concurrently developed as complimentary nondestructive evaluation (NDE) techniques for quality control and liferemain assessment of TBCs. This paper discusses recent achievements in understanding the residual stress, phase constituents, and electrochemical resistance (or capacitance) of TBC constituents—with an emphasis on the thermally grown oxide. Results from NDE by PSLS and EIS are correlated to the nano- and microstructural development of TBCs

The Non-Destructive and Nano-Microstructural Characterization of Thermal-Barrier Coatings

The durability of thermal barrier coatings (TBCs) plays an important role in the service reliability and maintainability of hot-section components in advanced turbine engines for aerospace and utility applications. Photostimulated luminescence spectroscopy (PSLS) and electrochemical impedance spectroscopy (EIS) are being concurrently developed as complimentary nondestructive evaluation (NDE) techniques for quality control and liferemain assessment of TBCs. This paper discusses recent achievements in understanding the residual stress, phase constituents, and electrochemical resistance (or capacitance) of TBC constituents—with an emphasis on the thermally grown oxide. Results from NDE by PSLS and EIS are correlated to the nano- and microstructural development of TBCs

Piezoacoustics for precision control of electrons floating on helium

Piezoelectric surface acoustic waves (SAWs) are powerful for investigating and controlling elementary and collective excitations in condensed matter. In semiconductor two-dimensional electron systems SAWs have been used to reveal the spatial and temporal structure of electronic states, produce quantized charge pumping, and transfer quantum information. In contrast to semiconductors, electrons trapped above the surface of superfluid helium form an ultra-high mobility, two-dimensional electron system home to strongly-interacting Coulomb liquid and solid states, which exhibit non-trivial spatial structure and temporal dynamics prime for SAW-based experiments. Here we report on the coupling of electrons on helium to an evanescent piezoelectric SAW. We demonstrate precision acoustoelectric transport of as little as ~0.01% of the electrons, opening the door to future quantized charge pumping experiments. We also show SAWs are a route to investigating the high-frequency dynamical response, and relaxational processes, of collective excitations of the electronic liquid and solid phases of electrons on helium.Comment: Main manuscript: 15 pages, 3 figures; Supplemental Information: 11 pages, 3 figures, 1 tabl

Effect of diabetic duration on hemorheological properties and platelet aggregation in streptozotocin-induced diabetic rats

Diabetes mellitus with abnormal glucose concentration is associated with changes in hemorheological properties, endothelial function, and platelets hyperactivity. Disturbances may significantly be responsible for diabetes-related vascular complications. In this study, hemorheological and hemodynamic properties were measured according to diabetic duration after streptozotocin treatment in rats. For ex vivo measurements, an extracorporeal model was adopted. Flow rate and blood viscosity were measured using a microfluidic device. Erythrocyte aggregation and morphological parameters of erythrocytes were measured by modified erythrocyte sedimentation rate and the phase-contrast holography under in vitro conditions. The platelet aggregation and mean pressure in the femoral artery were estimated under ex vivo conditions. Hemorheological properties including blood viscosity, erythrocyte aggregation and shape parameters for the control group are significantly different with those for diabetic groups. The changes with respect to diabetic duration were relatively unnoticeable. However, the platelet aggregation is strongly dependent on the diabetic duration. Based on these results, hyperglycemia exposure may induce hemorheological variations in early stages of diabetes mellitus. High platelet aggregation may become more pronounced according to the diabetic duration caused by variations in hemorheological properties resulting in endothelial dysfunction. This study would be helpful in understanding the effects of diabetic duration on biophysical properties.open11149sciescopu