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ShareScore release 0.9.0
Dataset results
11 results for “plant sounds”
Linked collectors and determiners for: University of Puget Sound, Slater Museum Herbarium Vascular Plants.
Natural history specimen data linked to collectors and determiners held within, "University of Puget Sound, Slater Museum Herbarium Vascular Plants". Claims or attributions were made on Bionomia by volunteer Scribes, <a href="https://bionomia.net/dataset/ee747f7d-daf9-4613-92f3-d7c2a356cae6">https://bionomia.net/dataset/ee747f7d-daf9-4613-92f3-d7c2a356cae6</a> using specimen data from the dataset aggregated by the Global Biodiversity Information Facility, <a href="https://gbif.org/dataset/ee747f7d-daf9-4613-92f3-d7c2a356cae6">https://gbif.org/dataset/ee747f7d-daf9-4613-92f3-d7c2a356cae6</a>. Formatted as a Frictionless Data package.
Recorded plant sounds from: Sounds emitted by plants under stress are airborne and informative
<p>Stressed plants show altered phenotypes, including changes in color, smell, and shape. Yet, airborne sounds emitted by stressed plants have not been investigated before. Here we show that stressed plants emit airborne sounds that can be recorded from a distance and classified. We recorded ultrasonic sounds emitted by tomato and tobacco plants inside an acoustic chamber, and in a greenhouse, while monitoring the plant's physiological parameters. We developed machine learning models that succeeded in identifying the condition of the plants, including dehydration level and injury, based solely on the emitted sounds. These informative sounds may also be detectable by other organisms. This work opens new avenues for understanding plants and their interactions with the environment and may have a significant impact on agriculture.</p>
Recorded plant sounds from: Sounds emitted by plants under stress are airborne and informative
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Dataset supporting Sound and Automated Synthesis of Digital Stabilizing Controllers for Continuous Plants
<p>Executable benchmarks and result data set for the experimental evaluation in our publication "Sound and Automated Synthesis of Digital Stabilizing Controllers for Continuous Plants" published at Hybrid Systems: Computation and Control (HSCC) 2017.</p> <p> </p> <p>Abstract:</p> <p>Modern control is implemented with digital microcontrollers, embedded within a dynamical plant that represents physical components.</p> <p>We present a new algorithm based on counter-example guided inductive synthesis that automates the design of digital controllers that are correct by construction. The synthesis result is sound with respect to the complete range of approximations, including time discretization, quantization effects, and finite-precision arithmetic and its rounding errors.</p> <p>We have implemented our new algorithm in a tool called DSSynth, and are able to automatically generate stable controllers for a set of intricate plant amodels taken from the literature within minutes.</p>
Data from: Plants’ ability to sense and respond to airborne sound is likely to be adaptive: reply to comment by Pyke et al.
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Data from: Increased sugar concentration in response to a wide range of pollinator sounds can be adaptive for the plant: Answer to Raguso et al.
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Identifying genes associated with sound vibration in plant
GEO Series GSE133325. Arabidopsis thaliana. 83 samples. Type: Expression profiling by high throughput sequencing; Genome binding/occupancy profiling by high throughput sequencing; Non-coding RNA profiling by high throughput sequencing.
Expression profiling by small RNA-seq for identifying miRNA associated with sound vibration in plant
GEO Series GSE133321. Arabidopsis thaliana. 18 samples. Type: Non-coding RNA profiling by high throughput sequencing.
Gene expression profiling study by RNA-seq for identifying genes associated with sound vibration in plant
GEO Series GSE133324. Arabidopsis thaliana. 29 samples. Type: Expression profiling by high throughput sequencing.
Expression data from leaves of tomato (Solanum lycopersicum L. cv. MicroTom) plants subjected to 1000 Hz sound vibration (at 90 dB for 2 h for 3 consecutive days) and/or inoculated with Pst DC300.
GEO Series GSE239448. Solanum lycopersicum. 24 samples. Type: Expression profiling by array.
ChIP-seq for identifying molecules associated with sound vibration in plant
GEO Series GSE133320. Arabidopsis thaliana. 36 samples. Type: Genome binding/occupancy profiling by high throughput sequencing.
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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.