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8 results for “approach velocity”
High-rate GNSS Raw Doppler Positive Impact on Cascading Filter-based Approach for Improving Real-time Transient Coseismic Velocities Modeling
<p>The high-rate GNSS average and instantaneous coseismic velocity waveforms for the 2016 Mw 6.6 Norcia earthquake and the 2011 Mw 9.1 Tohoku earthquake are included in this repository.</p>
Artificial intelligence-based parametrization of Michaelis–Menten maximal velocity: Toward in silico New Approach Methodologies (NAMs)
<p><span>The development of mechanistic systems biology models necessitates the utilization of numerous kinetic parameters once the enzymatic mode of action has been identified. Moreover, wet lab experimentation is associated with particularly high costs, does not adhere to the principle of reducing the number of animal tests, and is a time-consuming procedure. Alternatively, an artificial intelligence-based method is proposed that utilizes enzyme amino acid structures as input data. This method combines NLP techniques with molecular fingerprints of the catalyzed reaction to determine Michaelis–Menten maximal velocities (Vmax). The molecular fingerprints employed include RCDK standard fingerprints (1024 bits), MACCS keys (166 bits), PubChem fingerprints (881 bits), and E-States fingerprints (79 bits). These were integrated to produce reaction fingerprints. The data were sourced from SABIO RK, providing a concrete framework to support training procedures. After the data preprocessing stage, the dataset was randomly split into a training set (70%), a validation set (10%), and a test set (20%), ensuring unique amino acid sequences for each subset. The data points with structures similar to those used to train the model as well as uncommon reactions were employed to further test the model. The developed models were optimized during the training procedure to predict Vmax values efficiently and reliably. By utilizing a fully connected neural network, these models can be applied to all organisms. The amino acid proportions of enzymes were also tested, which revealed that the amino acid content was an unreliable predictor of the Vmax. During testing, the model demonstrated better performance on known structures than on unseen data. In the given use case, the model trained solely on enzyme representations achieved an R-squared of 0.45 on unseen data and 0.70 on known structures. When enzyme representations were integrated with RCDK fingerprints, the model achieved an R-squared of 0.46 for unseen data and 0.62 for known structures.</span></p>
Urban junco flight initiation distances correlate with approach velocities of anthropogenic sounds
Open the record for dataset details and reuse information.
Daily cross-correlation functions for "Time-lapse monitoring of seismic velocity associated with 2011 Shinmoe-dake eruption using seismic interferometry: an extended Kalman filter approach"
<p>The daily cross-correlation functions used in Nishida et al. 2020. We used three-component seismograms recorded at eight stations (six broadband sensors and two short-period sensors with a natural frequency of 1 Hz) from May 1st, 2010 to April 30th, 2018. Five stations were deployed by the Earthquake Research Institute, the University of Tokyo, and the other three were deployed by the National Research Institute for Earth Science and Disaster Prevention (NIED). The data can be found in the HDF5 file. You can also find a python code of an implementation of an extended Kalman filter/smoother for time-lapse monitoring of seismic velocity at GitHub (https://github.com/qnishida/eKlfS). The code estimates the temporal change in seismic velocities using this data set. </p>
Data from: Three-dimensional shape and velocity changes affect responses of a locust visual interneuron to approaching objects
Adaptive collision avoidance behaviours require accurate detection of complex spatiotemporal properties of an object approaching in an animal's natural, 3-dimensional environment. Within the locust, the lobula giant movement detector (LGMD) and its postsynaptic partner, the descending contralateral movement detector (DCMD) respond robustly to images that emulate an approaching 2-dimensional object and exhibit firing rate modulation correlated with changes in object trajectory. It is not known how this pathway responds to visual expansion of a 3-dimensional object or an approaching object that changes velocity, both of which representing natural stimuli. We compared DCMD responses to images that emulate the approach of a sphere with those elicited by a 2-dimensional disc. A sphere evoked later peak firing and deceased sensitivity to the ratio of the half size of the object to the approach velocity, resulting in an increased threshold subtense angle required to generate peak firing. We also presented locusts with a sphere that decreased or increased velocity against either a white or flow field background. A velocity decrease resulted in transition-associated peak firing followed by a firing rate increase that resembled the response to a constant, slower velocity. A velocity increase resulted in an earlier increase in the firing rate that was more pronounced with an earlier transition. For the flow field contrast used here, we observed no effect of background motion on responses to approaches along constant or changing velocities. These results further demonstrate that this pathway can provide motor circuits for behaviour with salient information about complex stimulus dynamics.
The Control of Velocity Variations in Turbidity Currents by Bed Erosion: A Froude number approach
<p>The data that support the findings of this study</p>
Data from: Three-dimensional shape and velocity changes affect responses of a locust visual interneuron to approaching objects
Open the record for dataset details and reuse information.
Assessing Force-velocity Profile: an Innovative Approach to Optimize Cardiac Rehabilitation in Coronary Patients
ClinicalTrials.gov study NCT04102410. IPD Sharing: NO. Countries: 1. Publications: 0.
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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.