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1,896 results for “call”
Cue the chorus: Canyon treefrog calling phenology on the falling limb of spring floods and warming nights
Phenology is the timing of life events tied to environmental or abiotic cues. We used autonomous recording units (ARUs) across spring-summer months in 2022 to capture breeding calls from canyon treefrog (Hyla arenicolor). ARUs were placed in perennial and intermittent stream reaches across five Wilderness Areas within the upper Verde River basin in Arizona. We monitored streams by installing stream flow gauges (water level recorders). Treefrogs call at relatively low flow after spring floods. This suggests that stream-dwelling anurans may breed in response to flooding followed by prolonged periods of base flows which could be important for tadpole metamorphosis. Implications for stream regulation suggest maintaining the magnitude and timing of flood pulse events can benefit recruitment of stream-breeding amphibians.
Calling activity of Birds in the White Mountain National Forest: Audio Recordings (2016 and 2018)
We collected 410 10-minute sound recordings of birds in and near the Hubbard Brook Experimental Forest in New Hampshire. Recordings, which encompassed most of the bird breeding season in each of two years, included 130,776 vocalizations from 46 taxa. In the associated publication, we report species lists, rarefaction curves, and vocalization descriptions. We also provide analyses of habitat associations, phenology, and spatial patterning in vocalization activity. These data were gathered as part of the Hubbard Brook Ecosystem Study (HBES). The HBES is a collaborative effort at the Hubbard Brook Experimental Forest, which is operated and maintained by the USDA Forest Service, Northern Research Station.
Calling activity of Birds in the White Mountain National Forest: Manifest of 99,778 acoustic recordings from bird plots in the Hubbard Brook Forest: 2016 - 2023
During 2016 - 2023, during the bird breeding season, we collected 99,778 files of bioacoustic recordings in and near the Hubbard Brook Experimental Forest in New Hampshire. Here, we provide a manifest of the sound files. Most files are one-hour recordings collected at 32 kHz and saved in FLAC format (~ 25 MB per file, ~ 13 TB total). Typical recording configuration was 05:00 - 08:00 and 17:30 - 20:30 local time. The full sound files have been saved in three respositories: two copies at Dartmouth College (Ayres lab) and one copy at the Macauley Library, Cornell Laboratory of Ornithology. The full sound files are available upon request. The file attributes within the manifest include date, start time, and recorder group: e.g., Main, 10ha, Oven, VW, AshBirch, and Ridge. Each recorder group had 5 - 20 recorders at plots separated by >100 m. Coordinates of each recorder are associated with plot names within metadata. The bird species expected to occur in these recordings are those from Holmes et al. (2021). These data were gathered as part of the Hubbard Brook Ecosystem Study (HBES). The HBES is a collaborative effort at the Hubbard Brook Experimental Forest, which is operated and maintained by the USDA Forest Service, Northern Research Station. Holmes, R., S. Sillett, and M. Hallworth. 2021. Bird species recorded within the Hubbard Brook Experimental Forest and vicinity (1963-2020; updated January 2021). ver 1. Environmental Data Initiative. https://doi.org/10.6073/pasta/da6cbb1ed8142d52a9d72762983742d8 (Accessed 2024-10-24).
Assembly and variant calling results of strain mixtures of HCMV
<p>The tgz files contain the assembly contigs of 10 different assemblers and variant calling results of 6 callers on the strain mixture dataset of the HCMV virus. </p>
I-BiDaaS - TID - Synthetic Call Centre Data
<p>This is a simulated dataset based on both real phone interactions and conversations usually performed by real call centres. It is comprised of several simulated customer interactions with an agent representative, both roles performed by actors. Phone call recordings are performed using different mobile and landline devices. The scripting, both from customer and agent, aims to develop typical scenarios by telco-oriented call centre operations. Both raw waveform recordings and speech transcription are provided. The latter as obtained by an automatic speech recognition (ASR) prototype developed by TID. The word segmentation timestamps are also provided for those recognized. Additionally, a confidence score is also provided per token basis.</p>
Enhanced Bug Prediction in JavaScript Programs with Hybrid Call-Graph Based Invocation Metrics (Training Dataset)
<p>This dataset consists of multiple files which contain bug prediction training data.</p> <p>The entries in the dataset are JavaScript functions either being buggy or non-buggy. Bug related information was obtained from the project EsLint contained in BugsJS (https://github.com/BugsJS/eslint). The buggy instances were collected throughout the lifetime of the project, however we added non-buggy entries from the latest version which is tagged as fix (entries which were previously included as buggy were not included as non-buggy later on).</p> <p>The dataset is based on hybrid call graphs which are constructed by https://github.com/sed-szeged/hcg-js-framework. The result of this tool is a call graph where the edges are associated with a confidence level which shows how likely the given edge is a valid call edge.</p> <p>We used different threshold values from which we considered the edges to be valid. The following threshold values were used:</p> <ul> <li>0.00</li> <li>0.05</li> <li>0.20</li> <li>0.30</li> </ul> <p>The prefix in the dataset file names are coming from the used threshold. The the datasets include coupling metrics NII (Nubmer of Incoming Invocations) and NOI (Number of Outgoing Invocations) which were calculated by a static source code analyzer called SourceMeter. Hybrid counterparts of these metrics (HNII and HNOI) are based on the given threshold values.</p> <p>There are four variants for all of these datasets:</p> <ul> <li>Both static (NII, NOi) and hybrid (HNII, HNOI) coupling metrics are included with additional static source code metrics and information about the entries (file without any postfix). Column contained only in this dataset are: <ul> <li>ID</li> <li>Name</li> <li>Longname</li> <li>Parent ID</li> <li>Component ID</li> <li>Path</li> <li>Line</li> <li>Column</li> <li>EndLine</li> <li>EndColumn</li> </ul> </li> <li>Both static (NII, NOi) and hybrid (HNII, HNOI) coupling metrics are included with additional static source code metrics (file with '_h+s' postfix)</li> <li>Only static (NII, NOI) coupling metrics are included with additional static source code metrics (file with '_s' postfix)</li> <li>Only hybrid (HNII, HNOI) coupling metrics are included with additional static source code metrics (file with '_h' postfix)</li> </ul> <p>Static source code metrics which are contained in all dataset are the following:</p> <ul> <li>McCC - McCabe Cyclomatic Complexity</li> <li>NL - Nesting Level</li> <li>NLE - Nesting Level Else If</li> <li>CD - Comment Density</li> <li>CLOC - Comment Lines of Code</li> <li>DLOC - Documentation Lines of Code</li> <li>TCD - Total Comment Density (Comment Lines in an emedded function will be also considered)</li> <li>TCLOC - Total Comment Lines of Code (Comment Lines in an emedded function will be also considered)</li> <li>LLOC - Logical Lines of Code (Comment and empty lines not counted)</li> <li>LOC - Lines of Code (Comment and empty lines are counted)</li> <li>NOS - Number of Statements</li> <li>NUMPAR - Number of Parameters</li> <li>TLLOC - Logical Lines of Code (Lines in embedded functions are also counted)</li> <li>TLOC - Lines of Code (Lines in embedded functions are also counted)</li> <li>TNOS - Total Number of Statements (Statements in embedded functions are also counted)</li> </ul>
6 Things To Check Before Calling An HVAC Pro
<p>Summer is halfway to its end and yet some household <a href="https://www.benairconditioning.com.au/">air conditioning Wollongong</a> units are malfunctioning. But before you even panic, you should take note of these things to check before calling an HVAC pro.</p> <p> </p>
Underlying data - Results from the Open Call: How Citizens can participate in solar energy research?
<p>Underlying data to the "Results from the Open Call: How Citizens can participate in solar energy research?" @</p> <pre>https://zenodo.org/record/3554901#.YAgimxaCE2w</pre> <p>Answers to the online survey in "Call for ideas_answers online_survey.xlsx"</p> <p>Notes from the World Cafe and other meetings from the secretaries: "notes_MMLs_GRECO_2019.pdf</p> <p> </p>
A call to eradicate non-inclusive terms from science
<p>Source code and data associated with a commentary (Khan, 2021; eLife) that shows an increase of non-inclusive terms with racial connotations used in life-science literature and calls for action to make science inclusive for all.</p>
FIGURE 1 in The last scream: the distress call of a probably extinct Brazilian anuran (Holoaden bradei Lutz, 1958)
FIGURE 1. Spectrogram (above) and oscillogram (below) of two distress calls of Holoaden bradei. One call with ascendantdescendant modulation (A) and another with slight modulation along its duration, except for the final portion, where it is observable a strong descendant modulation (B).
FIGURE 1 in Redescription, distribution and mating call of Pristimantis colomai (Lynch and Duellman, 1997) (Anura, Craugastoridae)
FIGURE 1. Dorsal and ventral view of (A) adult male UVC 7195 and (B) adult female UVC 5859 (scale bar = 5 mm) of Pristimantis colomai; (C) mating call showing the oscilogram (above), spectrogram (below), and power spectrum; and (D) geographic distribution showing the type locality (black star), historical records (white dots), and new records reported in this study (red dots).
Evaluation of Android Malware Detection Based on System Calls - Dataset
<p>This is a data set accompanying a paper "Evaluation of Android Malware Detection Based on System Calls" published in the proceedings of the International Workshop on Security and Privacy Analytics, New Orleans, USA, 2016.</p> <p>See README.md for details of the data set.</p>
System Call Logs with Natural Random Faults: Experimental Design and Application
<p>In this work we present a large dataset for use in embedded systems research which has been gathered from a realistic development environment operating in the path of an accelerated neutron beam. The dataset contains traces with events from a real-time operating system as as user events from a safety critical application. All data is carefully timestamped and in human understandable form.</p>
Experimental evolution under varying sex ratio and behavioral plasticity in response to perceived competitive environment independently affect calling effort in male crickets
<p>The operational sex ratio (OSR) is a key component influencing the magnitude of sexual selection driving the evolution of male sexual traits, but males often also retain the ability to plastically modulate trait expression depending on the current environment. Here we employed an experimental evolution approach to determine whether the OSR affects the evolution of male calling effort in decorated crickets, a costly sexual trait, and whether plasticity in calling effort is altered by the OSR under which males have evolved. Calling effort of males from two selection regimes maintained at different OSRs over 18–20 generations (male- versus female-biased) was recorded at two different levels of perceived competition, in the absence of rivals or in the presence of an experimentally muted competitor. The effect of the OSR on the evolution of male calling effort was modest and in the opposite direction predicted by theory. Instead, the immediate competitive environment strongly influenced male calling effort as males called more in the presence of a rival, revealing considerable plasticity in this trait. This increased calling effort came at a cost, however, as males confined with a muted rival experienced significantly higher mortality.</p>
Data from: Not afraid of the Big Bad Wolf: calls from large predators do not silence mesopredators
<p>Large predators are known to shape the behavior and ecology of sympatric predators via conflict and competition, with mesopredators thought to avoid large predators, while dogs suppress predator activity and act as guardians of human property. However, interspecific communication between predators has not been well-explored and this assumption of avoidance may oversimplify the responses of the species involved. We explored the acoustic activity of three closely related sympatric canids: wolves <em>Canis lupus</em>, coyotes <em>Canis latrans</em>, and dogs <em>Canis familiaris</em>. These species have an unbalanced triangle of risk: coyotes, as mesopredators, are at risk from both apex-predator wolves and human-associated dogs, while wolves fear dogs, and dogs may fear wolves as apex predators or challenge them as intruders into human-allied spaces. We predicted that risk perception would dictate vocal response with wolves and dogs silencing coyotes as well as dogs silencing wolves. Dogs, in their protective role of guarding human property, would respond to both. Eleven passive acoustic monitoring devices were deployed across 13 nights in Central Wisconsin, and we measured the responses of each species to naturally occurring heterospecific vocalizations. Against our expectation, silencing did not occur. Instead, coyotes were not silenced by either species: when hearing wolves, coyotes responded at greater than chance rates and when hearing dogs, coyotes did not produce fewer calls than chance rates. Similarly, wolves responded at above chance rates to coyotes and at chance rates when hearing dogs. Only the dogs followed our prediction and responded at above chance rates in response to both coyotes and wolves. Thus, instead of silencing their competitors, canid vocalizations elicit responses from them suggesting the existence of a complex heterospecific communication network.</p>
Fastq files for benchmarking somatic variant calling pipelines
<p>The <a href="https://download.imgag.de/public/validation_dataset_somatic/readme.html" target="_blank" rel="noopener">original .bam files</a> were provided by <a href="https://www.medizin.uni-tuebingen.de/de/das-klinikum/mitarbeiter/profil/3377" target="_blank" rel="noopener">Marc Sturm</a> from the <a href="https://www.medizin.uni-tuebingen.de/de/das-klinikum/einrichtungen/institute/medizinische-genetik-und-angewandte-genomik" target="_blank" rel="noopener">Institut für Medizinische Genetik und Angewandte Genomik at the University Clinic Tübingen.</a></p> <p>The files were transformed into .fq.gz files using the <a href="https://github.com/nf-core/bamtofastq" target="_blank" rel="noopener">nf-core/bamtofastq pipeline.</a> All information on the pipeline run can be found in the <a href="../api/records/10805134/draft/files/execution_report_2024-03-11_11-44-17.html/content" target="_blank" rel="noopener noreferrer">execution_report_2024-03-11_11-44-17.html</a>. The FASTQ files for the normal sample were directly uploaded to <a href="https://osf.io/cduyq/files/onedrive">the corresponding osf project</a>.</p> <p> </p> <p> </p>
Call data records
<p>This is a pre-processed subset of the call data records dataset from the <a href="https://arxiv.org/abs/1210.0137">Data for Development: the D4D Challenge on Mobile Phone Data</a>.</p> <p>The dataset consists of 8 time series of 3336 time steps sampled at hourly resolution. The 8 time series represent:</p> <ol> <li>The number of incoming calls in the area covered by the antenna.</li> <li>The volume in minutes of the incoming calls in the area covered by the antenna.</li> <li>The number of outgoing calls in the area covered by the antenna.</li> <li>The volume in minutes of the outgoing calls in the area covered by the antenna.</li> <li>The sine of the hour of the day when the telephone activity has been registered.</li> <li>The cosine of the hour of the day when the telephone activity has been registered.</li> <li>The sine of the day of the week when the telephone activity has been registered.</li> <li>The cosine of the day of the week when the telephone activity has been registered.</li> </ol> <p>This <a href="https://imgur.com/a/e3INnkG">image</a> shows the first 500 hours in each time series (time series 5-6 and 7-8 are plot together).</p> <p> </p> <p> </p>
Fig 1 in Effect of traffic noise on Scinax nasicus advertisement call (Amphibia, Anura)
Fig 1. Noise backgrounds and Scinax nasicus (Cope, 1862) call parameters at reference (Site A) and noisy environments (Site B). Amplitude (oscillograms A1, B1) and frequency (spectrograms A2, B2) of the environments. Amplitude (oscillograms A3, B3) and frequency (spectrograms A4, B4) of the advertisement frog's call.
Fig 2 in Effect of traffic noise on Scinax nasicus advertisement call (Amphibia, Anura)
Fig 2. Non-metric multidimensional scaling (NMDS) ordination of call variables of Scinax nasicus (Cope, 1862) adult males in natural (filled circles, Site A) and noisy environments (empty circles, Site B) Sites. The minimum frequency and duration as well as the displayed note pulse of the frogs call were different between the Sites in the first dimension.
Figure 4 in Calling behavior in virgin females of Diatraea saccharalis (Fabricius, 1794) (Lepidoptera: Crambidae) in laboratory
Figure 4. Calling number of one, two and three- days- old Diatraea saccharalis virgin females. / Número de llamados de hembras vírgenes de Diatraea saccharalis de uno, dos y tres días de edad. * Error bars indicate standard error.
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.