Find research datasets worth reusing
Search datasets from major research repositories and use ShareScore to quickly assess how well each record supports discovery, access, and reuse.
1,986
datasets available to search
ShareScore release 0.9.0
Dataset results
1,986 results for “valve”
TriBEL Registry: National Belgian Registry of Percutaneous Tricuspid Valve Repair Using a Transcatheter Edge-to-edge Repair Technique
ClinicalTrials.gov study NCT05577078. IPD Sharing: Not stated. Countries: 0. Publications: 0.
General Anesthesia Versus Loco-Regional Anesthesia for Transcarotid Trancatheter Aortic Valve Replacement
ClinicalTrials.gov study NCT06870734. IPD Sharing: UNDECIDED. Countries: 0. Publications: 0.
All Women Comparing Self-expanding ALLEGRA Valve to Any Other Balloon-expandable Valve
ClinicalTrials.gov study NCT05989074. IPD Sharing: UNDECIDED. Countries: 0. Publications: 0.
High-Flow Needleless Valve and DualCap Disinfection Devices Associate With Catheter-related Bloodstream Infection
ClinicalTrials.gov study NCT02990923. IPD Sharing: Not stated. Countries: 0. Publications: 0.
Effectiveness of Antibiotic Prophylaxis of Infective Endocarditis for Invasive Dental Procedures in Patients With Prosthetic Heart Valves and/or History of Infective Endocarditis
ClinicalTrials.gov study NCT05613933. IPD Sharing: Not stated. Countries: 0. Publications: 0.
To Evaluate Safety and Effectiveness of Transcatheter Aortic Valve System in Patients With Severe Aortic Insufficiency
ClinicalTrials.gov study NCT05424653. IPD Sharing: Not stated. Countries: 0. Publications: 0.
Comparative Analysis of Stented Biological Prosthesis Versus Aortic Allograft in Patients With Degenerative Aortic Valve Disease
ClinicalTrials.gov study NCT07210541. IPD Sharing: NO. Countries: 0. Publications: 0.
Implantation of the Venus P-Valve™ in the Pulmonic Position in Patients With Native Outflow Tracts
ClinicalTrials.gov study NCT02846753. IPD Sharing: NO. Countries: 0. Publications: 0.
Assessment of the St. Jude Medical PorticoTM Re-sheathable Aortic Valve System - Alternative Access
ClinicalTrials.gov study NCT02088021. IPD Sharing: Not stated. Countries: 0. Publications: 0.
Gene expression in aortic aneurysms associated with tricuspid and bicuspid valves
GEO Series GSE5180. Homo sapiens. 25 samples. Type: Expression profiling by array.
Expression data of human aortic valve cusps
GEO Series GSE51472. Homo sapiens. 15 samples. Type: Expression profiling by array.
Hypoxic culture maintains cell growth of the primary human valve interstitial cells with stemness
GEO Series GSE183112. Homo sapiens. 6 samples. Type: Expression profiling by high throughput sequencing.
Development of heart valves requires Gata4 expression in endothelial-derived cells
GEO Series GSE5298. Mus musculus. 8 samples. Type: Expression profiling by array.
A HAND2 Cistrome Controls Heart Development and the Endothelial-Mesenchymal Transition during Cardiac Valve Formation
GEO Series GSE73368. Mus musculus. 4 samples. Type: Genome binding/occupancy profiling by high throughput sequencing.
Super-Enhancer-Associated Aortic Valve Stenosis Risk Locus 1p21.2 Alters NFATC2 Binding Site and Promotes Fibrogenesis [ATAC-Seq]
GEO Series GSE154510. Homo sapiens. 1 samples. Type: Genome binding/occupancy profiling by high throughput sequencing.
Gene expression profile of calcified and normal tricuspid aortic valves by RNA sequencing.
GEO Series GSE55492. Homo sapiens. 19 samples. Type: Expression profiling by high throughput sequencing.
A Model-based Prognostics Approach Applied to Pneumatic Valves
Within the area of systems health management, the task of prognostics centers on predicting when components will fail. Model-based prognostics exploits domain knowledge of the system, its components, and how they fail by casting the underlying physical phenomena in a physics-based model that is derived from first principles. Uncertainty cannot be avoided in prediction, therefore, algorithms are employed that help in managing these uncertainties. The particle filtering algorithm has become a popular choice for model-based prognostics due to its wide applicability, ease of implementation, and support for uncertainty management. We develop a general model-based prognostics methodology within a robust probabilistic framework using particle filters. As a case study, we consider a pneumatic valve from the Space Shuttle cryogenic refueling system. We develop a detailed physics-based model of the pneumatic valve, and perform comprehensive simulation experiments to illustrate our prognostics approach and evaluate its effectiveness and robustness. The approach is demonstrated using historical pneumatic valve data from the refueling system.
Prognostics for Ground Support Systems: Case Study on Pneumatic Valves
Prognostics technologies determine the health (or damage) state of a component or sub- system, and make end of life (EOL) and remaining useful life (RUL) predictions. Such infor- mation enables system operators to make informed maintenance decisions and streamline operational and mission-level activities. We develop a model-based prognostics method- ology for pneumatic valves used in ground support equipment for cryogenic propellant loading operations. These valves are used to control the ow of propellant, so failures may have a signi cant impact on launch availability. Therefore, correctly predicting when valves will fail enables timely maintenance that avoids launch delays and aborts. The approach utilizes mathematical models describing the underlying physics of valve degradation, and, employing the particle ltering algorithm for joint state-parameter estimation, determines the health state of the valve and the rate of damage progression, from which EOL and RUL predictions are made. We develop a prototype user interface for valve prognostics, and demonstrate the prognostics approach using historical pneumatic valve data from the Space Shuttle refueling system.
A Model-Based Prognostics Approach Applied to Pneumatic Valves
Within the area of systems health management, the task of prognostics centers on predicting when components will fail. Model-based prognostics exploits domain knowledge of the system, its components, and how they fail by casting the un- derlying physical phenomena in a physics-based model that is derived from first principles. Uncertainty cannot be avoided in prediction, therefore, algorithms are employed that help in managing these uncertainties. The particle filtering algorithm has become a popular choice for model-based prognostics due to its wide applicability, ease of implementation, and support for uncertainty management. We develop a general model- based prognostics methodology within a robust probabilistic framework using particle filters. As a case study, we consider a pneumatic valve from the Space Shuttle cryogenic refuel- ing system. We develop a detailed physics-based model of the pneumatic valve, and perform comprehensive simulation experiments to illustrate our prognostics approach and evalu- ate its effectiveness and robustness. The approach is demon- strated using historical pneumatic valve data from the refuel- ing system.
Application of Model Based Prognostics to Pneumatic Valves in a Cryogenic Propellant Loading Testbed
Pneumatic-actuated valves are critical components in many applications, including cryogenic propellant loading for space operations. For these components, failures need to be predicted so that components can be repaired to ensure mission success, i.e., health monitoring and fault prognostics is required. In order to develop, test, mature, and deploy valve prognostics algorithms, we have developed a testbed for pneumatic valves used in cryogenic service for propellant loading operations, in which we can inject controlled damage pro files and observe its effects on valve operation. In this paper, we focus on the prognostics of a continuously-controlled pneumatic valve. We describe the construction of the testbed, the fault injection mechanisms, and the model-based valve prognostics algorithms. Experimental results from the testbed demonstrate successful prediction of valve failure.
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.