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Figure 2 in Assessing the taxonomic status of tropical frogs through bioacoustics: geographical variation in the advertisement calls in the Eleutherodactylus discoidalis species group (Anura)
Figure 2. Oscillogram and sound spectrogram of the advertisement call of: (A) Eleutherodactylus cruralis from Rurrenabaque, Amazonian rainforest; (B) E. cf. cruralis from Bellavista Mountains; (C) E. cf. cruralis from La Hoyada; (D) Eleutherodactylus discoidalis from Campos de Pinos; (E) Eleutherodactylus ibischi from Samaipata Road; (F) Eleutherodactylus madidi from Eslabón.
Figure 4 in Assessing the taxonomic status of tropical frogs through bioacoustics: geographical variation in the advertisement calls in the Eleutherodactylus discoidalis species group (Anura)
Figure 4. Scatterplot for (A) number of pulses and call length, (B) dominant frequency and number of pulses, and (C) dominant frequency and call length of species and populations of the Eleutherodactylus discoidalis group. Lines correspond to normally distributed probability ellipses (0.99, N = 194). BV, Eleutherodactylus cf. cruralis from the Bellavista Mountains; EC, Eleutherodactylus cruralis; ED, Eleutherodactylus discoidalis; EI, Eleutherodactylus ibischi; HO, Eleutherodactylus cf. cruralis from La Hoyada; EM, Eleutherodactylus madidi.
Figure 1 in Assessing the taxonomic status of tropical frogs through bioacoustics: geographical variation in the advertisement calls in the Eleutherodactylus discoidalis species group (Anura)
Figure 1. Map of the Andes of Bolivia showing the studied localities (see also Table 1). 1, Eslabón; 2, Chalalán; 3, Rurrenabaque; 4, Chapare, 500 m; 5, Mataracú; 6, La Hoyada; 7, Samaipata road; 8, Bellavista Mt; 9, Masicurí; 10, Campos de Pinos.
Zebra finch song and distance call amplitude measurements: A transmission experiment and observational transects in the natural environment
<p>Birdsong is typically seen as a long-range signal functioning in mate attraction and territory defense. Among birds, the zebra finch is the prime model organism in bioacoustics, yet almost exclusively studied in the lab. In the wild, however, zebra finch song differs strikingly from songbirds commonly studied in the wild as zebra finch males sing most after mating and in the absence of territoriality. Using data from the wild, we here provide an ecological context for a wealth of laboratory studies. By integrating calibrated sound recordings, sound transmission experiments and social ecology of zebra finches in the wild with insights from hearing physiology we show that wild zebra finch song is a very short-range signal with an audible range of about nine meters and that even the louder distance calls do not carry much farther (up to about fourteen meters). These integrated findings provide an ecological context for the interpretation of laboratory studies of this species and indicate that the vocal communication distance of the main laboratory species for avian acoustics contrasts strikingly with songbirds that use their song as a long-range advertisement signal.</p>
Dataset for Real and Virtual Backgrounds of Video Calls
<p>Video conferencing applications play an important role in our day-to-day life. They enable people to meet, work, and collaborate remotely, especially in circumstances where physical meetings are not possible (e.g., pandemic scenarios, long distances, etc.). However, such applications might invade people's privacy, such as disclosing their sensitive information. In this dataset, we recorded different video conferencing with diverse real and virtual backgrounds, changing subjects, lighting, and so on.</p> <p>If you want to use these datasets for non-commercial purposes, please cite the following papers:</p> <p>@article{nowroozi2020survey,<br> title={A survey of machine learning techniques in adversarial image forensics},<br> author={Nowroozi, Ehsan and Dehghantanha, Ali and Parizi, Reza M and Choo, Kim-Kwang Raymond},<br> journal={Computers \& Security},<br> pages={102092},<br> year={2020},<br> publisher={Elsevier}<br>}</p> <p> </p>
Video: Turkish National Advisory Group Meeting on Horizon Europe Solar Energy Call topics, 18 Nov. 2022
<p>Video of a 1 day open meeting to catalyze and support Turkish participation in a cluster of upcoming Horizon Europe Calls on Solar Energy.</p>
Data for: PerchPicker classifier model v7: A catalog of American silver perch (Bairdiella chrysoura) calls for machine learning
<p>This data repository contains labeled passive underwater acoustic data used to train and test the machine-learning model of Bohnenstiehl (in prep - 2023), <em>Automated cataloging of American silver perch (Bairdiella chrysoura) calls using machine learning</em>. The software accompanying this paper is known as PerchPicker (<a href="https://github.com/drbohnen/PerchPicker" rel="noopener">GitHub - drbohnen/PerchPicker)</a>, and the classifier model presented in the paper is v7. It consists of more than 6000 labeled perch and 6000 labeled other signals. Labeled scalogram images are provided, along with pressure-corrected waveforms (micro-Pascals) sampled at 24 kHz. Each waveform sample is 90 ms long. The center 30 ms of these waveform segments represent the portion of the signal used in training and testing the classifier model. Waveform data are provided in multiple formats: 1) MATLAB (.mat) files containing the 'perch' and 'other' waveforms stored in column format, and 2) individual .wav files, each containing a labeled waveform example. Codes are provided to demonstrate how these .wav files can be read into MATLAB and PYTHON. These labeled data can be used to re-train the PerchPicker model or develop alternative classifiers. </p>
REACH Incubator - open-call #2 Awarded SME dataset
<p>This file contain public dataset describing the awarded SME during the 2nd round of the REACH Incubator project.</p>
spindle cell variant diffuse large B-cell lymphoma (NGS annotation file; high confidence calls) hematolrep-2136295
<p>Diffuse large B-cell lymphoma with spindle cell morphology is a rare variant. We present the case of a 74-year-old male who initially presented with a right supraclavicular (lymph) node enlargement. Histological analysis showed a proliferation of spindle-shaped cells with narrow cytoplasms. An immunohistochemical panel was used to exclude other tumors, such as melanoma, carcinoma, and sarcoma. The lymphoma was characterized by a cell-of-origin subtype of germinal center B-cell-like (GCB) based on Hans’ classifier (CD10-negative, BCL6-positive, and MUM1-negative); EBER negativity, and the absence of BCL2, BCL6, and MYC rearrangements. Mutational profiling using a custom panel of 168 genes associated with aggressive B-cell lymphomas confirmed mutations in ACTB, ARID1B, DUSP2, DTX1, HLA-B, PTEN, and TNFRSF14. Based on the LymphGen 1.0 classification tool, this case had an ST2 subtype prediction. The immune microenvironment was characterized by moderate infiltration of M2-like tumor-associated macrophages (TMAs) with positivity of CD163, CSF1R, CD85A (LILRB3), and PD-L1; moderate PD-1 positive T cells, and low FOXP3 regulatory T lymphocytes (Tregs). Immunohistochemical expression of PTX3 and TNFRSF14 was absent. Interestingly, the lymphoma cells were positive for HLA-DP-DR, IL-10, and RGS1, which are markers associated with poor prognosis in DLBCL. The patient was treated with R-CHOP therapy, and achieved a metabolically complete response.</p> <p>Carreras J, Kikuti YY, Miyaoka M, Hiraiwa S, Tomita S, Ikoma H, Kondo Y, Ito A, Nagase S, Miura H, Roncador G, Colomo L, Hamoudi R, Campo E, Nakamura N. Mutational Profile and Pathological Features of a Case of Interleukin-10 and RGS1-Positive Spindle Cell Variant Diffuse Large B-Cell Lymphoma. <em>Hematology Reports</em>. 2023; 15(1):188-200. https://doi.org/10.3390/hematolrep15010020</p>
African elephants address one another with individually specific name-like calls
<div> <p>Personal names are a universal feature of human language, yet few analogs exist in other species. While dolphins and parrots address conspecifics by imitating the calls of the addressee, human names are not imitations of the sounds typically made by the named individual. Labeling objects or individuals without relying on imitation of the sounds made by that object or individual radically expands the expressive power of language. Thus, if non-imitative name analogs were found in other species, this could have important implications for our understanding of language evolution. Here, we present evidence that wild African elephants address one another with individually specific calls without imitation. We used machine learning to demonstrate that the receiver of a call could be predicted from the call's acoustic structure and found little evidence that calls addressed to a given receiver imitate the receiver's own calls. Moreover, elephants differentially responded to playbacks of calls originally addressed to them relative to calls addressed to a different individual, indicating that they can determine from a call's structure if it was addressed to them. Our findings offer the first evidence for a non-human species individually addressing conspecifics without imitating the receiver.</p> </div>
Data from: Both learning and syntax recognition are used by great tits when answering to mobbing calls
<p><span>Mobbing behavior, in addition to its complex cooperative aspects, is particularly suitable to study the mechanisms implicated in heterospecific communication. Indeed, various mechanisms ranging from pure learning to innate recognition have been proposed. One promising, yet understudied mechanism could be syntax recognition, especially given the latest works published on syntax comprehension in birds. In this experiment, we test whether great tits use both learning and syntax recognition when responding to heterospecifics. In the first part of the experiment, we demonstrate that great tits show different responses to the same heterospecific calls depending on their sympatric status. In a second part, we explore the impact of reorganizing the notes of the heterospecific mobbing calls to fit the syntax of great tits. Great tits showed an increased mobbing response toward the heterospecific calls when they shared their own call organization. Our results corroborate the recent finding that syntactic rules in bird calls may have a strong impact on their communication systems and enlighten how various mechanisms can be used by the same species to respond to heterospecific calls.</span></p>
The role of neighbour proximity and context on meerkat close call acoustic structure
<p><span>In many animal species, including humans, producer arousal state is considered a key modifier of vocal production and structure. Encoding of affective arousal state in vocalisations provides a rapid means of information transfer about an individual's internal state, potentially reflecting its response to external stimuli. Meerkats, Suricata suricatta, are a highly vocal species. They use close calls to maintain group cohesion while foraging. Due to their patchily distributed prey, motivation for neighbour proximity varies; being too close results in competition (increased arousal - aggression), while too far results in risks of losing the group and predation threats (increased arousal - fear). We investigated how neighbour proximity, and also behavioural, social and environmental context, influence the acoustic structure of wild wild meerkats' close calls. We found little effect of neighbour distance on the majority of the acoustic parameters measured. However, there was a consistent effect of the behavioural context in which the call was given across several acoustic parameters. Additionally, if the nearest neighbour was a pup calls became longer, lower and quieter. Overall, meerkat close calls potentially convey information on current behaviour and are modified in relation to social context. This highlights a potential mechanism in the diversification of acoustic signals. </span></p>
Aggregated Earnings Call Dataset
<p>Aggregated Earnings Call Dataset for the paper "FLAG: Financial Long Document Regression via AMR-based GNN"</p> <p>It contained earnings calls data, along with associated price data, that we collected from companies in the S&P 1500 Composite Index from 2010 to 2019.</p> <p>CSV files without "tech" in their filenames contain the full amount of earnings calls we collected, and CSV files with "tech" in their filenames contain the portion of the dataset from the technology sector, which we use in the experiments detailed in the paper.</p>
Fig. 7. Advertisement calls. A–B in Redescription of Adenomera diptyx (Boettger, 1885) (Anura, Leptodactylidae) and description of a closely related new species
Fig. 7. Advertisement calls. A–B. Sound file FZ-UNNE 0074 of Adenomera diptyx (Boettger, 1885). C–D. Sound file FZ-UNNE 0284 of A. guarani sp. nov. See Appendix 2 for locality data and voucher specimens. Oscillograms (A, C) show the distinctive note repetition rates in the two species. Call sections are equally scaled (ca 3 s; each tick mark corresponds to 0.5 s). Spectrograms and corresponding oscillograms (B, D) of the first note in A and C.
Data for: ToadFishFinder classifier model v4: A catalog of oyster toadfish (Opsanus tau) calls for machine learning
<p>This data repository contains labeled passive underwater acoustic data used to train and test the machine-learning model of Bohnenstiehl (in prep – 2023), <span>Automated cataloging of oyster toadfish (<em>Opsanus</em> <em>tau</em>) calls using template matching and machine learning</span>. The software accompanying this paper is known as ToadFishFinder, and the classifier model presented in the paper is v4. It consists of more than 10000 labeled toadfish and 10000 labeled other signals. Labeled spectrogram images are provided, along with pressure-corrected waveforms (micro-Pascals) sampled at 24 kHz. Each waveform sample is 1350 ms long. The center 850 ms of these waveform segments represent the portion of the signal used in training and testing the classifier model. Waveform data are provided in multiple formats: 1) MATLAB (.mat) files containing the 'boatwhistle' and 'other' waveforms stored in column format, and 2) individual .wav files, each containing a labeled waveform example. Codes are provided to demonstrate how these .wav files can be read into MATLAB and PYTHON. These labeled data can be used to re-train the ToadFishFinder model or develop alternative classifiers. </p>
Figures 1–3 in Individual variation in the advertisement call of Aplastodiscus albosignatus (Anura: Hylidae) is correlated with body size and environmental temperature
Figures 1–3. Location of the study area: (1) map of Brazil highlighting the state of Paraná; (2) map of Paraná indicating the study area; (3) map of Paraná highlighting the physiognomy of the vegetation.
Data and codes: Who is calling? Optimising source identification from marmoset vocalisations with hierarchical machine learning classifiers
<p>Data and codes that accompany the article titled "Who is calling? Optimising source identification from marmoset vocalisations with hierarchical machine learning classifiers".</p>
Fig. 5 in Calling songs of sympatric and allopatric populations of Cicada barbara and C. orni (Hemiptera: Cicadidae) on the Iberian Peninsula
Fig. 5. Scores of the first two PCA components extracted from a data matrix, which was composed of 9 acoustic variables measured for 158 individuals of Cicada barbara (Cb) and C. orni (Co) occurring allopatrically (allop) and sympatrically (symp).
Fig. 2 in Calling songs of sympatric and allopatric populations of Cicada barbara and C. orni (Hemiptera: Cicadidae) on the Iberian Peninsula
Fig. 2. Oscillograms (amplitude vs. time) and sonagrams (frequency vs. time) of the calling songs of Cicada barbara and C. orni.
Fig. 4 in Calling songs of sympatric and allopatric populations of Cicada barbara and C. orni (Hemiptera: Cicadidae) on the Iberian Peninsula
Fig. 4. Scatterplots of the number of syllables per second relative to temperature in Cicada barbara and C. orni and of both echeme duration and inter-echeme interval relative to temperature in C. orni.
ScienceDex guides
Understand access before you commit
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.