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309 results for “inspiration”
Hemodynamic data from the Inspired Therapeutics NeoMate Mechanical Circulatory Support System for neonates and infants as tested in static mock circulatory loops, dynamic mock circulatory loops, and acute animal studies
<p>Inspired Therapeutics (Merritt Island, FL) is developing a mechanical circulatory support (MCS) system designed as a single driver with interchangeable, extracorporeal, magnetically levitated pumps. The NeoMate system design features an integrated centrifugal rotary pump, motor, and controller that will be housed in a single compact unit. Conceptually, the primary innovation of this technology will be the combination of disposable, low-cost pumps for use with a single, multi-functional, universal controller to support multiple pediatric cardiopulmonary indications. In response to the paucity of clinically available pediatric devices, Inspired Therapeutics is specifically targeting the underserved neonate and infant heart failure (HF) patient population first. In this article, we present the development of the prototype Inspired Therapeutics NeoMate System for pediatric left ventricular assist device (LVAD) support, and feasibility testing in static mock flow loops (H-Q curves), dynamic mock flow loops (hemodynamics), and in an acute healthy ovine model (hemodynamics and clinical applicability). The resultant hydrodynamic and hemodynamic data demonstrated the ability of this prototype pediatric LVAD and universal controller to function over a range of rotary pump speeds (500-6000 RPM), to provide pump flow rates of up to 2.6 L/min, and to volume unload the left ventricle in acute animals. Key engineering challenges observed and proposed solutions for the next design iteration are also presented.</p>
Numenorean Blade (Inspiration)
A sword inspired by Numenorean types (From Tolkien's fantasy). Source: Objaverse 1.0 / Sketchfab
Source research data for the article titled "A Nature-Inspired Approach to Energy-Efficient Relay Selection in Low-Power Wide-Area Networks (LPWAN)".
<p>The source research data set developed and utilized while working on the article "A Nature-Inspired Approach to Energy-Efficient Relay Selection in Low-Power Wide-Area Networks (LPWAN)" for Sensors SI. The data set includes simulation results from OMNeT++ and the data to evaluate the parameters of the algorithms.</p>
Supplementary footage for ctenophore-inspired soft robotic platform
<p>These three folders contain supplementary footage for “Encoding spatiotemporal asymmetry in artificial cilia with a ctenophore-inspired soft-robotic platform”.</p> <p>“Phase-averaged” contains gifs of phase averaged horizontal component of velocity (u), velocity magnitude, and vorticity. Note the folder naming convention denotes the shape of the propulsor, followed by the number of magnets on the timing belt (low or high phase lag), followed by the beat frequency.</p> <p>“PIV” contains videos of the flow fields computed with Particle Image Velocimetry. The horizontal component of velocity and vorticity are included for each propulsor shape, phase lag, and beat frequency listed above.</p> <p>“Raw_footage” contains videos of the raw footage used for kinematics and PIV.</p>
Urocanic acid as a novel scaffold for next-gen nature-inspired sunscreens: I. Electronic laser spectroscopy under isolated conditions - dataset
Open the record for dataset details and reuse information.
Repeatability materials for paper "Database-Inspired Optimizations for Statistical Analysis"
<p>This repository contains files to replicate experiments in our paper "Database-Inspired Optimizations for Statistical Analysis", in particular data derived from the American Community Survey (ACS). Experiment scripts to use these files are here: https://scm.cwi.nl/DA/raaql-paper-experiments</p>
Study on bio-inspired feet based on the cushioning and shock absorption characteristics of ostrich foot
<p>The African ostrich (<em>Struthio camelus</em>) perennially living in deserts is outstanding with remarkable speed, exceptional endurance and continuous locomotion. As the main actuator of high-speed running, the ostrich feet possess excellent cushioning and shock absorption capabilities. In this study, based on the elastic modulus scales and assembly modes of soft tissues and the functions of the metatarsophalangeal (MTP) joint, eight bio-inspired feet were designed by an engineering method. With the peak acceleration as the index, the cushioning performances of different bio-inspired feet on loose sand or solid ground were compared through impact tests at different heights and verified by simulating the impact processes of the bio-inspired feet on loose sand on the finite element software Abaqus. Meanwhile, the stress distribution and deformation of each component of the bio-inspired feet were also clarified. The 15-15-15 HA (hardness unit) bio-inspired feet showed lower peak acceleration and thereby better cushioning performance, but larger deformation, less-uniform stress distributions and thereby lower stability than the 15-35-55 HA bio-inspired feet. Sensitivity analyses showed the cushioning capacity of the bio-inspired feet was comparable to that of the ostrich foot when the material (elastic modulus) and spring (stiffness coefficient) were properly selected. In fact, the silicon rubbers with different hardness levels which simulate the elasticity modulus scales of the toe pad, fascia and skin, and the spring mechanism which simulates the functions of the MTP joint, work as an “integrated system”of cushioning and shock absorption.</p>
Urocanic acid as a novel scaffold for next-gen nature-inspired sunscreens: II. Time-resolved spectroscopy under solution conditions - dataset
Open the record for dataset details and reuse information.
Dataset - Hand-inspired flying grasper
<p>Dataset for manuscripts "Hand-inspired flying grasper".</p> <p>The file 'data_analysis.zip' contains the experimental data packages (rosbag format) for all the autonomous experiments in the the paper, which are recorded in the ROS system under Linux. By running the provided MATLAB-based code, all the data curves in the paper can be reproduced.</p> <p> </p>
Dataset - Hand-inspired Flying Grasper
<p>Dataset for manuscripts "Hand-inspired Flying Grasper".</p> <p>The file 'data_bags.zip' contains the experimental data packages (rosbag format) for all the autonomous experiments in the paper, which are recorded in the ROS system under Linux. By running the provided MATLAB-based code, all the data curves in the paper can be reproduced.</p> <p> </p>
Deep Learning for Structure-Preserving Universal Stable Koopman-Inspired Embeddings for Nonlinear Canonical Hamiltonian Dynamics
<p>This dataset provides python implementation of the paper: Deep Learning for Structure-Preserving Universal Stable Koopman-Inspired Embeddings for Nonlinear Canonical Hamiltonian Dynamics, which is available on arXiv https://arxiv.org/abs/2308.13835.</p>
Bio-inspired Interlocking Micro-Patterning for Tunable, Switchable and Selective Adhesion in Wet and Dusty Environments
<p>Abstract of the related article: Achieving adhesion under unfavourable conditions, such as when van der Waals interaction is not available or in dust environments, is crucial in applications ranging from surgical sutures to wound-healing tapes, underwater adhesives, robotic grippers, and space grasping.<br>Interestingly, plants, animals, and microorganisms living in such environmental conditions, show surface morphological traits optimised to achieve mechanical interlocking. Thus, they achieve an effective work of adhesion thanks to the interplay of friction and interfacially-storeable elastic energy, which otherwise typically suppress adhesion.<br>In this work, we provide the design and fabrication fundamentals for achieving tailorable, switchable and robust mechanical adhesion under a general environmental condition, such as wet or dusty, bio-mimicking natural solutions.<br>A theoretical framework for the design of mechanical adhesion, based on mean field continuum contact mechanics, is suggested, and validated experimentally. This study can pave the way for the development of new technologies, to be employed in situations where conventional adhesives may be ineffective, such as for surfaces exposed to water, solvent vapors, lubricants, high temperatures, dusty environments, high vacuum, or aerospace applications, or processes where switching and selective adhesion is needed such as grasping and sorting applications in semiconductor industry.</p> <p>The files are named after the numbering of the Figure in which they are used.<br>Description of the scripts as following:</p> <p>- FigureS5_ABCD.nb is a mathematica script to visualize the normalized single pair interaction for spherical interlockers, relating the dimensionless axial force to the dimensionless axial position.</p> <p>- Figure6_AnalyticalModel.nb is used to obtain the theoretical probability density function of the distance between microstructures when they follow a uniform distribution over a circular area.</p> <p>-Figure5.nb is a mathematica script used to perform a parametric study on double conical interlockers, varying the R/I_0 ratio, in approach/recede motion in dilute/dense conditions</p> <p>-Figure6_xyz_123.py is a python script used to perform Montecarlo simulations, it computes the histogram of distances between points randomly spread (lattice distributed, uniformly distributed, quasi-random distributed) on a unit circle.</p> <p>-FigureS8B.nb is a mathematica script used to average all the force contributions during the detachment phase of double conical patterned surfaces in order to get the Equation of state of the system, relating the normalized pressure to the out of plane axial displacement.</p> <p>- FigureS5_EFGH.nb is a mathematica script used to perform a parametric study on spherical interlockers, varying the friction coefficient value, in approach/recede motion in dilute/dense conditions.</p> <p>- Figure4.nb is a mathematica script used to perform a parametric study on spherical interlockers, varying the R/I_0 ratio in dilute/dense conditions.</p> <p>- FigureS6_EFGH.nb is a mathematica script used to perform a parametric study on double conical interlockers, varying the friction coefficient value, in approach/recede motion in dilute/dense conditions.</p> <p>- FigureS8A.nb is a mathematica script used to average all the force contributions during the attachment phase of double conical patterned surfaces in order to get the Equation of state of the system, relating the normalized pressure to the out of plane axial displacement.</p> <p>- FigureS2.rar is a folder with images of the dust characterization (coarse.tif; fine.tif; extrafine.tif) with python scripts to analyse the said images (ImageAnalysis.py) and extract the histogram of the equivalent particle diameter (HistogramPlot.py)</p> <p><br>- FigureS6_ABCD.nb is a mathematica script to visualize the normalized single pair interaction for double conical interlockers, relating the dimensionless axial force to the dimensionless axial position.</p> <p> </p> <p> </p> <p> </p>
Hydroacoustic and hydrodynamic investigation of bio-inspired leading-edge tubercles on marine ducted thrusters
<p>Underwater radiated noise (URN) has a negative impact on the marine acoustic environment where it can disrupt marine creature's basic living functions such as navigation and communication. To control the ambient ocean noise levels due to human activities, international governing bodies such as the International Maritime Organisation (IMO) have issued non-mandatory guidelines to address this issue. Under such framework, the hydroacoustic performance of marine vehicles has become a critical factor to be evaluated and controlled throughout the vehicles' service life in order to mitigate the URN level and the role humankind plays in the ocean. This study aims to apply leading-edge (LE) tubercles of the Humpback whales' pectoral fins to a benchmark ducted propeller to investigate its potential in noise mitigation. This was conducted using CFD, where the high-fidelity Improved Delayed Detached Eddy Simulations (IDDES) in combination with the porous Ffowcs-Williams Hawkings (FW-H) acoustic analogy was used to solve the hydrodynamic flow-field and propagate the generated noise to the far-field. It has been found that the LE tubercles have shown promising noise mitigation capabilities in the far-field, where the OASPL at J = 0.1 was reduced to a maximum of 3.4dB with a maximum of 11dB reduction in certain frequency ranges at other operating conditions. Based on detailed flow analysis researching the fundamental vortex dynamics, this noise reduction is shown to be due to the disruption of the coherent turbulent wake structure in the propeller slipstream causing the acceleration in the dissipation of turbulence and vorticity induced noise.</p>
Data used in real world-inspired experiments for submission titled "Causal Contextual Bandits with Targeted Interventions"
<p>Data used in real world-inspired experiments for submission titled "Causal Contextual Bandits with Targeted Interventions".</p>
Model 4 dataset for the manuscript "Improving trajectory calculations by FLEXPART 10.4+ using deep learning inspired single image superresolution"
<p>Model 4 dataset for the manuscript "Improving trajectory calculations by FLEXPART 10.4+ using deep learning inspired single image superresolution"</p>
Model 2 dataset for the manuscript "Improving trajectory calculations by FLEXPART 10.4+ using deep learning inspired single image superresolution"
<p>Dataset produced by the model 2 neural network for the manuscript "Improving trajectory calculations by FLEXPART 10.4+ using deep learning inspired single image superresolution"</p>
Training image dataset of strawberry flowers for new Nature Inspired Detector (NID)
<p>This dataset consists of images of 4 white-flowering strawberry cultivars: <em>F. x ananassa</em> <em>‘Seascape’, ‘Fort Laramie’,</em> and <em>'Hecker',</em> and<em> F. Vesca. </em>The image's size is 416x416 with the following augmentations: horizontal and vertical flip, rotate ±90-degrees, rotate ±15-degrees, sheer ±15-degrees vertical and horizontal, noise 5%, and blur 5px. Labels for both Faster R-CNN and Yolo V5 are included. </p>
Unlocking the Predictive Power of Quantum-Inspired Representations for Intermolecular Properties in Machine Learning
<p>Dataset associated with the manuscript entitled "Unlocking the Predictive Power of Quantum-Inspired Representations for Intermolecular Properties in Machine Learning". </p> <p>See Readme file (markdown format) for details on how the data is structured in the "database" file.</p>
Support data for "Maritime radar odometry inspired by visual odometry"
<p>This is reduced resolution example data to accompany the code at `https://github.com/hflemmen/radar_odometry`.</p>
Code for Edge Learning Using a Fully Integrated Neuro-Inspired Memristor Chip
<p>Code for Edge Learning Using a Fully Integrated Neuro-Inspired Memristor Chip.</p> <p>These codes can also be accessed through GitHub: https://github.com/Tsinghua-LEMON-Lab/software_edge_learning_memristor_chip.git. </p>
ScienceDex guides
Understand access before you commit
These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.