Computational evaluation of inferior vena cava filters through computational fluid dynamics methods

Numerical simulation is growing in its importance toward the design, testing and evaluation of medical devices. Computational fluid dynamics and finite element analysis allow improved calculation of stress, heat transfer, and flow to better understand the medical device environment. Current research focuses not only on improving medical devices, but also on improving the computational tools themselves. As methods and computer technology allow for faster simulation times, iterations and trials can be performed faster to collect more data. Given the adverse events associated with long-term inferior vena cava (IVC) filter placement, IVC filter design and device evaluation are of paramount importance. This work reviews computational methods used to develop, test, and improve IVC filters to ultimately serve the needs of the patient

The SWELL1-LRRC8 complex regulates endothelial AKT-eNOS signaling and vascular function

The endothelium responds to numerous chemical and mechanical factors in regulating vascular tone, blood pressure, and blood flow. The endothelial volume-regulated anion channel (VRAC) has been proposed to be mechanosensitive and thereby sense fluid flow and hydrostatic pressure to regulate vascular function. Here, we show that the leucine-rich repeat-containing protein 8a, LRRC8A (SWELL1), is required for VRAC in human umbilical vein endothelial cells (HUVECs). Endothelial LRRC8A regulates AKT-endothelial nitric oxide synthase (eNOS) signaling under basal, stretch, and shear-flow stimulation, forms a GRB2-Cav1-eNOS signaling complex, and is required for endothelial cell alignment to laminar shear flow. Endothelium-restricte

Small molecule SWELL1 complex induction improves glycemic control and nonalcoholic fatty liver disease in murine Type 2 diabetes

Type 2 diabetes is associated with insulin resistance, impaired pancreatic β-cell insulin secretion, and nonalcoholic fatty liver disease. Tissue-specific SWELL1 ablation impairs insulin signaling in adipose, skeletal muscle, and endothelium, and impairs β-cell insulin secretion and glycemic control. Here, we show that

High contrast imaging at the LBT: the LEECH exoplanet imaging survey

In Spring 2013, the LEECH (LBTI Exozodi Exoplanet Common Hunt) survey began its $\sim$130-night campaign from the Large Binocular Telescope (LBT) atop Mt Graham, Arizona. This survey benefits from the many technological achievements of the LBT, including two 8.4-meter mirrors on a single fixed mount, dual adaptive secondary mirrors for high Strehl performance, and a cold beam combiner to dramatically reduce the telescope's overall background emissivity. LEECH neatly complements other high-contrast planet imaging efforts by observing stars at L' (3.8 $\mu$m), as opposed to the shorter wavelength near-infrared bands (1-2.4 $\mu$m) of other surveys. This portion of the spectrum offers deep mass sensitivity, especially around nearby adolescent ($\sim$0.1-1 Gyr) stars. LEECH's contrast is competitive with other extreme adaptive optics systems, while providing an alternative survey strategy. Additionally, LEECH is characterizing known exoplanetary systems with observations from 3-5$\mu$m in preparation for JWST.Comment: 12 pages, 5 figures. Proceedings of the SPIE, 9148-2

Capturing dynamical correlations using implicit neural representations

The observation and description of collective excitations in solids is a fundamental issue when seeking to understand the physics of a many-body system. Analysis of these excitations is usually carried out by measuring the dynamical structure factor, S(Q, $\omega$), with inelastic neutron or x-ray scattering techniques and comparing this against a calculated dynamical model. Here, we develop an artificial intelligence framework which combines a neural network trained to mimic simulated data from a model Hamiltonian with automatic differentiation to recover unknown parameters from experimental data. We benchmark this approach on a Linear Spin Wave Theory (LSWT) simulator and advanced inelastic neutron scattering data from the square-lattice spin-1 antiferromagnet La$_2$NiO$_4$. We find that the model predicts the unknown parameters with excellent agreement relative to analytical fitting. In doing so, we illustrate the ability to build and train a differentiable model only once, which then can be applied in real-time to multi-dimensional scattering data, without the need for human-guided peak finding and fitting algorithms. This prototypical approach promises a new technology for this field to automatically detect and refine more advanced models for ordered quantum systems.Comment: 12 pages, 7 figure

3D Heisenberg universality in the Van der Waals antiferromagnet NiPS3_3

Van der Waals (vdW) magnetic materials are comprised of layers of atomically thin sheets, making them ideal platforms for studying magnetism at the two-dimensional (2D) limit. These materials are at the center of a host of novel types of experiments, however, there are notably few pathways to directly probe their magnetic structure. We report the magnetic order within a single crystal of NiPS$_3$ and show it can be accessed with resonant elastic X-ray diffraction along the edge of the vdW planes in a carefully grown crystal by detecting structurally forbidden resonant magnetic X-ray scattering. We find the magnetic order parameter has a critical exponent of $\beta\sim0.36$, indicating that the magnetism of these vdW crystals is more adequately characterized by the three-dimensional (3D) Heisenberg universality class. We verify these findings with first-principle density functional theory, Monte-Carlo simulations, and density matrix renormalization group calculations

Gender Differences in Russian Colour Naming

In the present study we explored Russian colour naming in a web-based psycholinguistic experiment (http://www.colournaming.com). Colour singletons representing the Munsell Color Solid (N=600 in total) were presented on a computer monitor and named using an unconstrained colour-naming method. Respondents were Russian speakers (N=713). For gender-split equal-size samples (NF=333, NM=333) we estimated and compared (i) location of centroids of 12 Russian basic colour terms (BCTs); (ii) the number of words in colour descriptors; (iii) occurrences of BCTs most frequent non-BCTs. We found a close correspondence between females’ and males’ BCT centroids. Among individual BCTs, the highest inter-gender agreement was for seryj ‘grey’ and goluboj ‘light blue’, while the lowest was for sinij ‘dark blue’ and krasnyj ‘red’. Females revealed a significantly richer repertory of distinct colour descriptors, with great variety of monolexemic non-BCTs and “fancy” colour names; in comparison, males offered relatively more BCTs or their compounds. Along with these measures, we gauged denotata of most frequent CTs, reflected by linguistic segmentation of colour space, by employing a synthetic observer trained by gender-specific responses. This psycholinguistic representation revealed females’ more refined linguistic segmentation, compared to males, with higher linguistic density predominantly along the redgreen axis of colour space

Testing the data framework for an AI algorithm in preparation for high data rate X-ray facilities

The advent of next-generation X-ray free electron lasers will be capable of delivering X-rays at a repetition rate approaching 1 MHz continuously. This will require the development of data systems to handle experiments at these type of facilities, especially for high throughput applications, such as femtosecond X-ray crystallography and X-ray photon fluctuation spectroscopy. Here, we demonstrate a framework which captures single shot X-ray data at the LCLS and implements a machine-learning algorithm to automatically extract the contrast parameter from the collected data. We measure the time required to return the results and assess the feasibility of using this framework at high data volume. We use this experiment to determine the feasibility of solutions for `live' data analysis at the MHz repetition rate