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65 results for “Axles”
Truck Axle Detection
<p>This dataset was created to train a neural network to recognize truck axles, applied to videos recorded in a highway in the State of São Paulo, Brazil. This is still a work in progress and will be updated regularly. More info can be found in our <a href="https://www.researchgate.net/lab/Andre-Luiz-Cunha-Lab">Researchgate Lab Page</a> or on our OrcID Profiles.</p> <p>The dataset includes 1737 cropped images of truck axles, divided in two folders:</p> <ul> <li>Axle_Dark - Images of shadowed or dark truck axles, with few features and details visible. <ul> <li>1034 images</li> <li>Format: JPEG</li> <li>Resolution: Various, 96dpi</li> </ul> </li> <li>Axle_Clear - Images of clear truck axles, with visible details and features. <ul> <li>703 images</li> <li>Format: JPEG</li> <li>Resolution: Various, 96dpi</li> </ul> </li> <li>Naming pattern: <video_name>_<color|gray>-<Region_of_Interest_ID>-<truck_ID>_<axle_number>.jpg</li> </ul> <p>If this dataset helps in any way your research, please feel free to contact the authors. We really enjoy knowing about other researcher's projects and how everybody is making use of the images on this dataset. We are also open for collaborations and to answer any questions.</p>
Data sets of multi-body models for conventional, articulated, and equidistant-axles trains and single span bridges
<p>Information about characteristics of multi-body models of conventional, articulated, and equidistant-axles trains.</p> <p>Information about bridge data set, used for vehicle-bridge interaction investigations.</p>
Data set of axle loads and distances for operating passenger and freight trains for development of load models
<p>Train data for moving load models of operating trains (5,007 passenger trains and 139,182 freight trains).</p> <ul> <li>axle distances [m] and axle loads [kN] for all trains included in zip-files as txt-files</li> <li>information on line categories (DIN EN 15528), loadcases and maximum speeds for passenger trains (and assignment to passenger train numbers in previous version of publication (used for development of load model)) in xlsx-file</li> </ul>
Virtual Axle Detector based on Analysis of Bridge Acceleration Measurements by Fully Convolutional Network
<p>We recorded the measurement data used in the present study on a single-span steel trough railway bridge located on a long-distance traffic line in Germany. The bridge is 18.4 m long in total with a free span of 16.4 m. A total of 10 seismic uniaxial accelerometers of the type PCB-39B04 (PCB Synotech) with a sensitivity of 1000 mV/g (±10\%), a broadband resolution of 0.000003 gRMS, a measurement range of ±5 gpk and a frequency range of 0.06 to 450 Hz (±5\%) were installed. The measurements are triggered via the rising slope of the wheel load measuring point G1, the measurements from the ring buffer are stored from ten seconds before the trigger together with the 50 seconds long measurement after the triggering. The recorded signals thus all have a length of 60 seconds. All sensor signals were recorded with a sampling frequency of fs = 600 Hz using the catmanAP software and the CX22 data recorder connected to an MX1601B universal amplifier and an MX1616B strain gauge amplifier (all products are from HBK). </p>
MH 1993.10.6 South Indian Carved Axle Cap
Culture: South Indian Title: carved wood axle cap (one of a pair) Materials: Carved wood Accession Number: MH 1993.10.6 Credit Line: Gift of Susan and Bernard N. Schilling (Susan Eisenhart, Class of 1932) View this object on the Collections Database: http://museums.fivecolleges.edu/detail.php?museum=all&t=objects&type=all&f=&s=mh+1993+10+3&record=18 Photographs and photogrammetry by Laura Shea (Digital Collections Coordinator and Museum Photographer), Mount Holyoke College Art Museum; Copyright info: Contact the Mount Holyoke College Art Museum South Hadley, Massachusetts, USA 01075 413-538-2245 http://www.mtholyoke.edu/artmuseum/ The Mount Holyoke College Art Museum is dedicated to teaching and learning; therefore, we value your feedback and welcome any scholarly observations. Please feel free to contact us if you would like to learn more about the objects you see here or to request 3D models of other objects in our collections. Source: Objaverse 1.0 / Sketchfab
Evaluation of Comparative Damaging Effects of Multiple Truck Axles for Flexible Pavements
<p>Corresponding data set for Tran-SET Project No. 17PUTA01. Abstract of the final report is stated below for reference:</p> <p>"This study aims at evaluating the effect of overlapping flexible pavement strain responses from truck axles that are not part of multiple axle configurations (i.e., tandem, triple and quad). For this purpose, a newly constructed pavement was instrumented with strain gauges installed at the bottom of the asphalt concrete base layer on US-287 south of Mansfield, TX. This pavement structure is typically used for medium- to high-volume roads in the South-Central region of the United States. The strain gauges were used to measure longitudinal and transverse strains under several passes of a test vehicle. This was a class 6 truck with a steering axle load of 56.9 kN (12.8 kips) and a tandem drive axle load of 161.9 kN (36.4 kips). The speed and the lateral position of the vehicle were recorded for each test vehicle pass. Sufficient quantities of the top two layers of asphalt concrete were obtained during construction to allow dynamic modulus testing in the laboratory. The general-purpose finite element program Abaqus was used to model the instrumented pavement section and compute the longitudinal and transverse strains at the location of the strain gauges. In the analysis, the asphalt concrete layers were modeled as visco-elastic materials. The Abaqus estimated strains were found in good agreement with the measured strains. Both the field measurements and the finite element analysis showed that the strains under the passing of the steering axle were of similar magnitude as the strains under the passing of the rear tandem axle. The measured transverse strains were in general slightly larger than the corresponding longitudinal strains. This can be attributed to the accumulation of strain from the front axle and the rear axle that takes place only in the transverse direction. However, the finite element model computed higher strains in the longitudinal direction than in the transverse direction. These findings suggest the need to account for the overlap in strain responses from the steering and the following axles of trucks. Furthermore, findings suggest that both the longitudinal and the transverse strain responses need to be considered in evaluating the fatigue damage impacted from trucks."</p>
Cabozantinib in Patients With RET Fusion-Positive Advanced Non-Small Cell Lung Cancer and Those With Other Genotypes: ROS1 or NTRK Fusions or Increased MET or AXL Activity
ClinicalTrials.gov study NCT01639508. IPD Sharing: Not stated. Countries: 1. Publications: 3.
Study of Demarcation Line Depth in Transepithelial Versus Epithelium-off Accelerated Cross-linking (AXL) in Keratocouns
ClinicalTrials.gov study NCT04045626. IPD Sharing: NO. Countries: 1. Publications: 1.
CAB-AXL-ADC Safety and Efficacy Study in Adult and Adolescent Patients With Sarcoma
ClinicalTrials.gov study NCT03425279. IPD Sharing: UNDECIDED. Countries: 3. Publications: 0.
Liquid Biopsy and Pancreas Cancer: Detection of AXL(+) CTCs (CTC-AXL-PANC)
ClinicalTrials.gov study NCT05346536. IPD Sharing: NO. Countries: 1. Publications: 27.
Enapotamab Vedotin (HuMax-AXL-ADC) Safety Study in Patients With Solid Tumors
ClinicalTrials.gov study NCT02988817. IPD Sharing: Not stated. Countries: 6. Publications: 0.
Phase 1/2 Study of TP-0903 (an Inhibitor of AXL Kinase) in Patients With Previously Treated CLL
ClinicalTrials.gov study NCT03572634. IPD Sharing: NO. Countries: 1. Publications: 0.
AXL-TBK1 driven AKT3 activation promotes metastasis
GEO Series GSE274874. Homo sapiens. 5 samples. Type: Expression profiling by high throughput sequencing.
Transcriptomic analysis of orthotopic pancreatic tumors treated by Axl inhibitor TP-0903 or combination with chemo/immunotherapy using the nCounter PanCancer Immune Profiling panel (Nanostring Technol
GEO Series GSE185110. Mus musculus. 36 samples. Type: Expression profiling by array.
The AXL-PYK2-PKCα axis as a nexus of stemness circuits in TNBC
GEO Series GSE166609. Homo sapiens. 4 samples. Type: Expression profiling by high throughput sequencing.
Gas6-Axl signaling drives oral regenerative wound repair
GEO Series GSE287384. Mus musculus. 4 samples. Type: Other.
AXL mediates resistance to PI3Kα inhibition by activating the EGFR/PKC/mTOR axis in head and neck and esophageal squamous cell carcinomas.
GEO Series GSE61515. Homo sapiens. 9 samples. Type: Expression profiling by high throughput sequencing.
The TAM receptor tyrosine kinases Axl and Mer drive the phagocytic differentiation of tissue-resident macrophages
GEO Series GSE192363. Mus musculus. 12 samples. Type: Expression profiling by high throughput sequencing.
Inhibition of AXL Receptor Tyrosine Kinase Enhances Brown Adipose Tissue Functionality in mice [HiSeq]
GEO Series GSE231469. Mus musculus. 10 samples. Type: Expression profiling by high throughput sequencing.
Bulk RNA-Seq to study the response of cDC2 and Axl+DC to HIV-1 infection
GEO Series GSE189727. Homo sapiens. 24 samples. Type: Expression profiling by high throughput sequencing.
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DANDI Archive for NWB datasets
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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.