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1,308 results for “Vehicle”
Expression data of glioblastoma cells with Crizotinib acute and chronic treatment vs its own vehicle control
GEO Series GSE113961. Homo sapiens. 4 samples. Type: Expression profiling by array.
Transcriptome analysis of xenograft tumors treated with vehicle control or CBL0137
GEO Series GSE140652. Homo sapiens. 6 samples. Type: Expression profiling by high throughput sequencing.
Expression data of U87 MG glioblastoma cells with vehicle or with 30nM Panobinostat treatment for 3 weeks
GEO Series GSE103961. Homo sapiens. 2 samples. Type: Expression profiling by array.
Microarray profiling of rats treated for 21 days with Lithium chloride (0.2% in chow), Lamotrigine (30 mg/kg), or appropriately matched vehicles
GEO Series GSE66276. Rattus norvegicus. 60 samples. Type: Expression profiling by array.
Gene expression data from THP-1 cells exposed to exosomes from acetaminophen-treated or vehicle-treated hepatocytes or corresponding mock- or medium-controls
GEO Series GSE125690. Homo sapiens. 24 samples. Type: Expression profiling by array.
Genome-wide map of Acetyl-H3K27 marked chromatin in pancreatic cancer cells treated with vehicle and acetate under low pH condition
GEO Series GSE160365. Homo sapiens. 4 samples. Type: Genome binding/occupancy profiling by high throughput sequencing.
Expression data from renal cancer patient-derived xenograft tumor treated with temsirolimus or vehicle
GEO Series GSE133446. Homo sapiens. 9 samples. Type: Expression profiling by array.
ISHM for Launch Vehicles
This is a collection of different presentations that cover a range of topics within ISHM for Launch Vehicles
Vehicle-Level Reasoning Systems: Integrating System-Wide data to Estimate Instantaneous Health State
One of the primary goals of Integrated Vehicle Health Management (IVHM) is to detect, diagnose, predict, and mitigate adverse events during the flight of an aircraft, regardless of the subsystem(s) from which the adverse event arises. To properly address this problem, it is critical to develop technologies that can integrate large, heterogeneous (meaning that they contain both continuous and discrete signals), asynchronous data streams from multiple subsystems in order to detect a potential adverse event, diagnose its cause, predict the effect of that event on the remaining useful life of the vehicle, and then take appropriate steps to mitigate the event if warranted. These data streams may have highly non-Gaussian distributions and can also contain discrete signals such as caution and warning messages which exhibit non-stationary and obey arbitrary noise models. At the aircraft level, a Vehicle-Level Reasoning System (VLRS) can be developed to provide aircraft with at least two significant capabilities: improvement of aircraft safety due to enhanced monitoring and reasoning about the aircraft’s health state, and also potential cost savings through Condition Based Maintenance (CBM). Along with the achieving the benefits of CBM, an important challenge facing aviation safety today is safeguarding against system- and component-level failures and malfunctions. Citation: A. N. Srivastava, D. Mylaraswamy, R. Mah, and E. Cooper, “Vehicle Level Reasoning Systems: Concept and Future Directions,” Society of Automotive Engineers Integrated Vehicle Health Management Book, Ian Jennions, Ed., 2011.
Health-Management Driven Control Reconfiguration Approach for Flight Vehicles
A prognostic system makes it possible to anticipate loss of functionality before it occurs with sufficient lead time to take actions that mitigate the impact of this loss. We focus on the forms of mitigation within the flight vehicle that influence the operational dynamics but do not directly amend the mission plan. Thus, we focus upon the reconfiguration of the feedback control strategy for the flight system. The high degree of complexity in the design and dynamics of modern aircraft is typically handled using a hierarchical control scheme in which there are several levels of control at increasing levels of responsibility: the component level, the subsystem level, and the system level. Our reconfiguration strategy involves mitigating problems that are detected at the component level at both the level in which the fault is detected and higher levels as well. There are, thus, two subproblems to the reconfiguration: (a) an adaptive control problem at the lower level to extend component life and derive new component performance limits, and (b) a supervisory control problem at the higher level to adapt the system controller to maximize system capability while respecting the performance limitations. Since our reconfiguration occurs in the context of a dynamic system, we need to respect the stability implications of the reconfiguration. To address this, we apply bandwidth analyses at the component level and the systems level in a robust performance context. A conservative criterion for stability is to impose rate limits for reconfiguration that insure that undesired, and possibly unmodeled, modes of behavior are not driven by reconfiguration activities. For specific hardware, extensions beyond this conservative approach may be warranted (e.g. to catch faulty behavior) and validated on a case-by-case basis, essentially by extending the component modeling to include a model of behavior under certain types of reconfiguration.
Draft genome sequences of Aspergillus and Penicillium species isolated from the International Space Station and Crew Resupply Vehicle Capsule
Genome sequencing and assembly of fungal isolates belonging to Penicilliium and Aspergillus genera isolated from International Space Station
A Recursive Receding Horizon Planning for Unmanned Vehicles
This paper proposes a recursive receding horizon path planning algorithm for unmanned vehicles in nonuniform environments. In the proposed algorithm, the map is described by grids in which nodes are defined on corners of grids. The planning algorithm considers the map as four areas, namely, implementation, observation, explored, and unknown. The Implementation area is a subset of the Observation area, whereas the Explored area is the union of all the previous Observation areas. The path is planned with a receding horizon planning strategy to generate waypoints and in-between map updates. When a new map update occurs, the path is replanned within the current Observation area if necessary. If no such path exists, the search is extended to the Explored area. Paths can be planned by recursively searching available nodes inside the Explored area that can be connected to available nodes on the boundary of the Explored area. A robot platform is employed to conduct a series of experiments in a laboratory environment to verify the proposed path planning algorithm.
Algorithms and their Impact on Integrated Vehicle Health Management - Chapter 7
This chapter discussed some of the algorithmic choices one encounters when designing an IVHM system. While it would be generally desirable to be able to pick a particular set of algorithms for a particular problem, the reality is a bit more complex. Depending on the budget, the performance requirements, the computational constraints, sensor availability, access to historical data, operational and environmental conditions, robustness to changing system configurations, algorithm maintenance needs, etc., no one algorithm will perform best in all situations. Indeed, it is necessary to evaluate these constraints during the algorithm design process and determine the best choice on a case-by-case analysis. The trade-offs between different choices are very real, and sometimes no solution can be found, which means that some of the constraints have to be relaxed. The simplest solution is generally preferred over a more complex one, but it is also important to consider that there is no free lunch. Finally, any health management solution also has to undergo verification and validation (V&V) and, in some cases, certification. Some of these issues are topics of other chapters in this book.
NASA 3D Models: Vehicle Assembly Building (VAB)
The Vehicle Assembly Building (VAB) is one of the largest buildings in the world. It was originally built for assembly of Apollo/Saturn vehicles and was later modified to support Space Shuttle operations. Polygons: 3528 Vertices: 3388
NASA 3D Models: Vehicle Assembly Building (VAB)
The Vehicle Assembly Building (VAB) is one of the largest buildings in the world. It was originally built for assembly of Apollo/Saturn vehicles and was later modified to support Space Shuttle operations. Polygons: 3528 Vertices: 3388
scRNA-seq data of spleen immune cells from Vehicle- and Glutoborin-treated mice
GEO Series GSE290269. Mus musculus. 2 samples. Type: Expression profiling by high throughput sequencing.
scRNA-seq of tumor-infiltrating CD45+ cells from B16-F10 tumor-bearing mice treated with vehicle and DOPAC.
GEO Series GSE287577. Mus musculus. 2 samples. Type: Expression profiling by high throughput sequencing.
RNA-seq of OT-I cells co-cultured with vehicle, TANs or TAMos under OVA257-264 stimulation
GEO Series GSE224871. Mus musculus. 6 samples. Type: Expression profiling by high throughput sequencing.
Strain-specific CNV in zebrafish treated with PCB-126, vehicle control, or untreated
GEO Series GSE110763. Danio rerio. 54 samples. Type: Genome variation profiling by array.
Gene expression of cardiomyocytes isolated from vehicle and Doxorubicin challenged mice
GEO Series GSE223698. Mus musculus. 6 samples. Type: Expression profiling by high throughput sequencing.
ScienceDex guides
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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.