Find research datasets worth reusing

Displacement measurement via self mixing interferometry and neural network training set

Self mixing interferometry is a simple and robust sensing method which can be used (among other things) to measure the displacement of a target along the light propagation axis. While conceptually simple, the actual use of this method is less straightforward than originally envisioned because reconstructing the target displacement from the interferometric signal is often tricky. A small neural network can do this task very well after proper training, as described in [10.1364/OE.419844]. This data set was used to train the network in that work (after data augmentation). It consists of a python dictionary with two keys: `truth` and `signal`. The `truth` part is a  195011-elements long numpy array corresponding to the displacement of the target in units of wavelength per 1.024 ms. The `signal` part is the interferometric signal corresponding to the displacement. It is arranged in a (195011,256,1) numpy array. Each segment of length 256 corresponds to the interferometric signal acquired during a 1.024 ms time window.  For instance, the displacement value in `truth[618]` corresponds to the interferometric signal segment `signal[618,:,0]`.

PsPM-LSOA: Pupil size response, SCR, EMG, ECG and respiration measurement from a classical (Pavlovian) discriminant delay fear conditioning task

This dataset includes eye tracker (including pupillometry), skin conductance, EMG, ECG and respiratory measurements. Also included are task information, keypress responses, keypress response times and key correctness for each of 22 healthy unmedicated participants (13 females and 9 males aged 25.3 +/- 4.3 years) participating in a classical (Pavlovian) discriminant delay fear conditioning task. CS consists of two sine tones with constant frequency (135 Hz or 300 Hz). Assignment of CS frequency to CS-/CS+ is randomised across participants. US is a train of electric square pulses delivered with a constant current stimulator (Digitimer DS7A, Digitimer, Welwyn Garden City, UK) on participants' dominant forearm through a pin-cathode/ring-anode configuration. SOA betwen the CS and US is 7.5 s. The ITI is randomly determined on each trial to be 10.0 +/- 1.4 s.

Shear-wave splitting measurements for a 10-year catalogue in Taupō volcano

The dataset provided includes seismic anisotropy results using a 10-year catalogue around Taupō volcano (January 2010  to December 2019). For the seismic anisotropy measurements, we used seismic data from 23 stations managed by GeoNet. The earthquake catalogue for this dataset was determined by Illsley-Kemp et al. (2021) using matched-filtered earthquake detection (Chamberlain & Townend, 2018). The earthquake templates for the matched-filtered detection were obtained from the GeoNet catalogue with revised manual picks.  In case you use this data, please cite the following publications: Bakkar, H. (2022). Seismic anisotropy and time-frequency analyses during Taupō's 2019 unrest [Master's thesis, Victoria University of Wellington]. Illsley-Kemp, F., Barker, S. J., Wilson, C. J. N., Chamberlain, C. J., Hreinsd ́ottir, S., Ellis, S., Hamling, I. J., Savage, M. K., Mestel, E. R., & Wadsworth, F. B. (2021). Volcanic unrest at Taupo ̄ volcano in 2019: Causes, mechanisms and implications. Geochemistry, Geophysics, Geosystems, e2021GC009803. The data is presented in .csv files, in the same format as MFAST output,  (http://mfast-package.geo.vuw.ac.nz), in which each column is: 1. Name of the event. 2. Station code. 3. Station latitude. 4. Station longitude. 5. Event identification number. 6. Year. 7. Julian day on which the event occurred, with decimal digits giving the fraction of the day. 8. Earthquake latitude in degrees. 9. Earthquake longitude in degrees. 10. Distance between earthquake and station (km). 11. Earthquake depth (km). 12. Earthquake magnitude. 13. Back azimuth in degrees. 14. Initial polarisation of the shear wave in degrees. 15. Error of the initial polarisation in degrees, one standard deviation. 16. Start time of the selected measurement window in seconds, relative to the start of the seismogram at t = 0. 17. End time of the selected measurement window in seconds, relative to the start of the seismogram at t = 0. 18. Not used 19. Not used 20. Signal to noise ratio for this event. 21. Delay tome between fast and slow shear wave in seconds. 22. Delay time between fast and slow shear wave in seconds. 23. Angle of the orientation of the fast shear wave (φ), in degrees from North. 24. Error of φ in degrees, one standard deviation. 25. Angle of incidence at the station, measured against a horizontal plane in degrees, where 0 means vertical incidence. 26. Not used 27. Type of measurement. This field contains the measurement code that is used, the number of measurement window start times and the number of window end times. 28. Not used 29. Not used 30. Nyquist frequency of the event in Hz. 31. Evaluation of the measurement quality. 32. Lower corner frequency of the bandpass filter in Hz. 33. Higher corner frequency of the bandpass filter in Hz. 34. Angle between the initial polarisation and the fast orientation in degrees. 35. Not used 36. Not used 37. The maximum value of the eigenvalue of the corrected covariance matrix. 38. The number of degrees of freedom in the measurement.       39. The minimum value of the eigenvalue of the covariance matrix before it was scaled to have the 95% confidence level set to 1. 40. The S-wave travel time between the earthquake and the station. 41. The dominant frequency in the S wave, determined from the frequency at the maximum spectral amplitude.

Air Quality - Genova City - Various measurement points

Concentration of various pollutants in several measurement points located in the area of the City of Genova. Source: <a href="http://www.cartografiarl.regione.liguria.it/SiraQualAria/script/Pub2AccessoDatiAria.asp">http://www.cartografiarl.regione.liguria.it/SiraQualAria/script/Pub2AccessoDatiAria.asp</a>

Meteo - Genova City- Various measurement points

Weathear condtions in several measurement points located in the area of the City of Genova Source: <a href="https://dati.comune.genova.it/Web_Service_meteo/handle_soap_request.php?mode=no_wsdl&action=read_json">https://dati.comune.genova.it/Web_Service_meteo/handle_soap_request.php?mode=no_wsdl&action=read_json</a> Column order: datetime;temperature;wind_chill;humidity;wind_speed;wind;wind_dir;pressure;rain;dew_point;rain_uh

Measuring the flexibility achieved by a change of tariff

<ul> <li>Name: Measuring the flexibility achieved by a change of tariff.</li> <li>Summary: This dataset contains the results of a survey carried out by the Spanish electricity retailer GoiEner to assess the impact that a change of from a "flat rate" tariff towards a "time of use" tariff have. Two files are provided: <ul> <li>The results of the survey merged with a summary of the energy consumption of the clients before and after the change of tariff.</li> <li>The questions of the survey.</li> </ul> </li> <li>License: CC-BY-SA</li> <li>Acknowledge: These data have been collected in the framework of the WHY project. This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 891943.</li> <li>Disclaimer: The sole responsibility for the content of this publication lies with the authors. It does not necessarily reflect the opinion of the Executive Agency for Small and Medium-sized Enterprises (EASME) or the European Commission (EC). EASME or the EC are not responsible for any use that may be made of the information contained therein.</li> <li>Collection Date:</li> <li>Publication Date: December 1, 2022.</li> <li>DOI: 10.5281/zenodo.7382924</li> <li>Other repositories: None.</li> <li>Author: GoiEner, University of Deusto.</li> <li>Objective of collection: The objective of the data collected is to assess the impact that the change of tariff has on the clients of GoiEner. In particular, the following questions wanted to be answered: <ul> <li>How much energy conservation can trigger a change of tariff?</li> <li>How much time flexibility could be trigger with a Time of Use Tariff?</li> <li>What are the main barriers to change the behavoiur?</li> <li>Are there any differences on behaviour depending on the socio-cultural-psycological profile of the consumers?</li> </ul> </li> <li>Description: The meaning of each column is described next: <ul> <li>Qx_y: Answers to the survey. See the survey file attached (in Spanish) for details.</li> <li>X.z: Answers to question "¿En qué rango de horas se realizan las siguientes acciones en el domicilio?". Sorted from left to right, top to bottom.</li> <li>Idioma: Languaje used to answer the survey.</li> <li>Desea.dar.su.CU: data used to de-anonymize the answers.</li> <li>{P,F,V}{19,20,21}: total energy consumed during the peak, flat and valley period of the day between 6/19 to 5/20 (19), 6/20 to 5/21 (20) and 6/21 to 5/22 (21).</li> <li>T{19,20,21}: total energy consumed between 6/19 to 5/20 (19), 6/20 to 5/21 (20) and 6/21 to 5/22 (21).</li> <li>kpi2_abs:  T20 - T21</li> <li>kpi2_rel: kpi2_abs / T20</li> <li>kpi1_{P,F,V}{19,20,21}:   {P,F,V}{19,20,21} / T{19,20,21}</li> <li>kpi1_{P,F,V}diff: kpi1_{P,F,V}19 - kpi1_{P,F,V}21</li> <li>T20DHS{19,20,21}: Cost of the energy of during the different periods using the last tariff.</li> <li>T20TD{19,20,21}: Cost of the energy of during the different periods using the new tariff.</li> <li>POWER_TARGET: Energy powerty rist indicator (https://powerpoor.eu/sites/default/files/2022-09/POWERPOOR%20D2.2%20POWER%20TARGET%20v1.0.pdf)</li> <li>TotalEnergyBudget: Self assessment of the energy budget of the house in Euros.</li> <li>Invoices20{20,21,22}: Amount of all the invoices for the house during the different periods.</li> <li>min30{in,pre,pst}: Cluster assigned depending on its electric behaviour pre-COVID, during the COVID lockdowns and post COVID lockdowns. See 10.5281/zenodo.7382818 for details.</li> </ul> </li> <li>5 star: ⭐⭐⭐</li> <li>Preprocessing steps: Data integration (from different sources from GoiEner services); data transformation (anonymization, unit conversion, metadata generation).</li> <li>Reuse: This dataset is related to datasets: <ul> <li>"A database of features extracted from different electricity load profiles datasets" (DOI 10.5281/zenodo.7382818), where time series feature extraction has been performed.</li> </ul> </li> <li>Update policy: There might be a single update in mid-2023 with a repetition of the survey as there have been another change of tariff in Spain.</li> <li>Ethics and legal aspects: The data provided by GoiEner contained values of the CUPS (Meter Point Administration Number), which are personal data. A pre-processing step has been carried out to replace the CUPS by random 64-character hashes.</li> <li>Technical aspects: the survey is provided as a PDF file and the data as a CSV file compressed with zstandard.</li> <li>Other: None.</li> </ul>

opencc-by-4.0Dec 2021View details →

Measurements of natural radioactivity levels and associated radiation hazard indices in Moringa plant leaf samples from selected areas in southern Ethiopia.

Moringa stenopetala (MS) is a multipurpose tree whose leaf is consumed by people of all ages in southern Ethiopia. In this study, natural radioactivity levels of 226Ra, 232Th, and 40K, as well as the related dangerous radiological characteristics, were measured on different sites of moringa samples using high-purity germanium (HPGe) gamma-ray spectrometry. Average activity concentrations of 226Ra, 232Th, and 40K in moringa leaves are found to be 0.49 ± 0.12, 3.84 ± 1.12, and 573.29 ± 26.79 Bq.kg-1, respectively. Moreover, the average values of the corresponding radiological parameters, Raeq, Hint, and annual effective dose (Eave) (sum), were also found to be 50.13 ± 3.79 Bq.kg-1, 0.136 ± 0.010, and 0.238 ± 0.089 mSvy-1, respectively. When the obtained results for all of the samples were compared to globally accepted criteria, they were discovered to be lower than the allowable world average levels. Furthermore, the lifetime cancer risk was revealed to be far lower than the allowable limit. According to the study, the risk of absorbing natural radionuclides from moringa leaf ingestion is insignificant. The findings can be utilized to create radiation safety norms and regulations for the use of moringa leaves as food and medication.

Combined fluorescence fluctuation and spectrofluorometric measure-ments reveal a red-shifted, near-IR emissive photo-isomerized form of Cyanine 5

This folder contains all raw data underlying the results presented in a manuscript, accepted for publication in International Journal of Molecular Sciences, and entitled:   Combined fluorescence fluctuation and spectrofluorometric measurements reveal a red-shifted, near-IR emissive photo-isomerized form of Cyanine 5   Authored by: Elin Sandberg 1, Joachim Piguet 1, Haichun Liu 1 and Jerker Widengren 1,*   1 Experimental Biomolecular Physics, Department of Applied Physics, Royal Institute of Technology (KTH), Stockholm, Sweden *  To whom correspondence should be addressed. Email: jwideng@kth.se. Tel: +46-8-7907813   The data files are grouped into the different techniques used to generate them, and refer to the figures/tables in the manuscript where the extracted results are presented.   ABSTRACT Cyanine fluorophores are extensively used in fluorescence spectroscopy and imaging. Upon continuous exciation, especially at excitation conditions used in single-molecule and super-resolution experiments, photo-isomerized states of cyanines easily reach population probabilies of around 50%. Still, effects of photo-isomerization are largely ignored in such experiments. Here, we studied the photo-isomerization of the pentamethine Cyanine 5 (Cy5) by two similar, yet complementary means to follow fluorophore blinking dynamics: fluorescence correlation spectroscopy (FCS) and transient state (TRAST) excitation-modulation spectroscopy. Additionally, we combined TRAST and spectrofluorimetry (spectral-TRAST), whereby emission spectra of Cy5 were recorded upon different rectangular pulse-train excitations. We also developed a framework for analyzing transitions between multiple emissive states in FCS and TRAST experiments, how the brightness of the different states is weighted, and what initial conditions that apply. Our FCS, TRAST and spectral-TRAST experiments showed significant differences in dark state relaxation amplitudes for different spectral detection ranges, which we attribute to an additional, red-shifted emissive photo-isomerized state of Cy5, not previously considered in FCS and single-molecule experiments. The photo-isomerization kinetics of this state indicate that it is formed under moderate excitation conditions, and its population and emission may thus deserve also more general consideration in fluorescence imaging and spectroscopy experiments.

opencc-by-4.0Aug 2022View details →

Data - Retrospective analysis of measures to reduce large whale entanglements in a lucrative commercial fishery

Datasets for the manuscript titled "Retrospective analysis of measures to reduce large whale entanglements in a lucrative commercial fishery" (<a href="https://doi.org/10.1016/j.biocon.2022.109880">https://doi.org/10.1016/j.biocon.2022.109880</a>).    Please see the README file for further information on each data file.

opencc-by-4.0Jun 2022View details →

Quantification of Error Sources with Inertial Measurement Units in Sports - Data and Matlab Scripts

Inertial measurement units (IMUs) offer the possibility to capture the lower body motions of players of outdoor team sports. However, various sources of error are present when using IMUs: the definition of the body frames, the soft tissue artefact (STA) and the orientation filer. Methods to minimize these errors are currently being used without knowing their exact influence on the various sources of errors. The goal of this study was to quantify each of the sources of error of an IMU separately. An optoelectronic system was used as a golden standard. Rigid marker clusters (RMCs) were designed to construct a rigid connection between the IMU and four markers. This allowed for the separate quantification of each of the sources of error. Ten subjects performed nine different trials, varying both in type of movement and in movement intensity. The error of the definition of the body frames (10.9-18.1 deg RMSD), the STA (3.6-9.4 deg RMSD) and the error of the orientation filter (2.8- 13.1 deg RMSD) were all quantified separately. The data and code to process the data can be found in this publication.

Whisker vibrations measured with acoustic methods

Original voltage traces measured with a mouse whisker of 21.5mm long that is consecutively trimmed.  Data are used for all figures in the manuscript

Dead wood in the forests of Northern Eurasian: field measurements database

Dead wood plays a substantial role in forest ecosystem functioning. However, the amount and dynamics of dead wood in the forests of Northern Eurasia are poorly understood. Here we present a database of field measurements of dead wood, collected from published sources and aggregated data from the Russian national forest inventory. The structure of dead wood by its components includes snags, logs, stumps, and the dry branches of living trees The database is intended to be used to assess the dead wood volume and the amount of dead wood in carbon units as part of the carbon budget calculation of forests at different scales. The database is a supplementary material in the following journal paper. Shvidenko, A.; Mukhortova, L.; Kapitsa, E.; Kraxner, F.; See, L.; Pyzhev, A.; Gordeev, R.; Fedorov, S.; Korotkov, V.; Bartalev, S.; Schepaschenko D. A Modelling System for Dead Wood Assessment in the Forests of Northern Eurasia. Forests 2023, 14, 45. https://doi.org/10.3390/f14010045

Estimated densities of activity from: Characterising diel activity patterns to design conservation measures: Case study of European bat species

Estimated densities of activity calculated in "Characterising diel activity patterns to design conservation measures: case study of European bat species" (see Materials and Methods for more information on these calculations). The files named "densitiyAllYear" correspond to the estimated densities based on our entire dataset. The files named "densitiySpring" correspond to the estimated densities based on a subset of our dataset comprising only monitoring carried out between 1 March and 21 June. The files named "densitiySummer" correspond to the estimated densities based on a subset of our dataset comprising only monitoring carried out between 22 June and 21 August. The files named "densitiyAutumn" correspond to the estimated densities based on a subset of our dataset comprising only monitoring carried out between 22 August and 31 October. The first column of each file ("PercentageNight") corresponds to the percentage of the night elapsed (0 % = sunset time, 100 % =  sunrise time), the second to the estimated activity density ("Density").

opencc-by-4.0Mar 2021View details →

MammalBase — Database of traits, measurements and diets of the species in class Mammalia

MammalBase is a database of traits, measurements and diets of the species in class Mammalia. It also provides Proximate Analysis data for several diet items. MammalBase aims to provide general information on mammals for broad-scale analyses in Macroecology, Palaeontology and mammalian Community structures. The database is maintained at the Natural Sciences Unit of the Finnish Museum of Natural History LUOMUS — a research institution under the University of Helsinki in Finland.

opencc-by-4.0Jul 2022View details →

Spectral Measurements of Parent Soils from Globally Important Dust Aerosol Entrainment Regions

Spectral data for the paper “Spectral Characterization of Parent Soils from Globally Important Dust Aerosol Entrainment Regions” submitted to the journal of JGR: Atmospheres article number: 2022JD037666. Visible, short-wave infrared (VSWIR) and longwave infrared (LWIR) reflectance spectra as well as longwave transmission spectra presented in that paper are included in this Zenodo repository. The spectral data are stored in CSV file format in columns and the first columns are the wavelengths. VSWIR reflectance: VSWIR was measured in the wavelength range between ~ 350 and 2500 nm using Spectral Evolution (SE), model RS-5400 portable spectroradiometer with a spectral resolution of 1.5 to 3.8 nm. Soil samples were placed in an aluminum holder and the reflectance spectra collected using a contact probe, equipped with an internal halogen light source. A reflectance spectrum for a spectralon white reference panel was obtained prior to each soil measurement for calibration. All soil reflectance spectra were automatically ratioed to that of the spectralon calibration target. All spectral measurements were converted to absolute reflectance using the correction for spectralon. To obtain adequate signal to noise ratio (SNR), 60 individual scans were averaged for each final output spectrum. LWIR reflectance: LWIR reflectance was measured in the wavelength range between ~ 2.5 and 25 µm using a benchtop Nicolet 380 Fourier Transform Infrared (FTIR) spectrometer. We used a diffuse reflectance attachment that holds the sample and reference plate horizontally. Gold was used as a reference reflectance standard, because it is highly reflective at all LWIR wavelengths. Once the reference background is collected, the loaded sample holder is placed into the FTIR device to measure the sample reflectance, which is automatically ratioed to the reflectance of the gold plate. This removes the effects caused by the instrument and by atmospheric gases in the instrument path length so that features in the final spectrum are solely due to the sample. To improve the SNR, we set the numbers of scans averaged for the samples and gold reference to 100 and 200, respectively. LWIR transmission: LWIR transmission was measured in the wavelength range between ~ 2.5 and 25 µm using a benchtop Nicolet 380 Fourier Transform Infrared (FTIR) spectrometer. First, we made soil-KBr pellets using 0.5 mg of soil and 200 mg of KBr blended using a clean mortar and pestle for 2 to 3 minutes to ensure uniform dispersion of mineral particles in the matrix. Pellet production was performed with the means of an evacuable KBr Die Kit and a CrushIR Digital Hydraulic Press from PIKE Technologies (Madison, WI, USA). The mixture was first transferred to the Die Kit which was then pressed under vacuum for about 4 to 5 minutes at a pressure of ~ 10 t cm-2, forming a hard disk 13 mm in diameter. Due to the hygroscopic nature of KBr, we pulled a vacuum on the pellet die for approximately 3 to 4 minutes prior to compression, and we immediately placed the pellets in a desiccant box, and then measured transmission within one or two hours of pellet creation. The pellet was attached to a self-adhesive sampling card and placed into the transmission holder. The resulting transmission spectrum for the sample is recorded with the dust-KBr mixture measurement being ratioed to that for an empty chamber, or blank reference. To avoid contamination of transmission spectra with ambient gases, the instrument was initially purged with dry air for at least 5 minutes, prior to each transmission collection. To increase the quality of the spectra and improve the SNR, the numbers of scans averaged were 200 for the blank reference and 100 for the samples.

Measurement of the albedo of red soil in Ghana in 2020

The albedo of red soil in Ghana was measured with an Albedometer in three different locations in 2020 following the ASTM Standard E1918-06. The dataset contains the calibration and the resolved measurements of the three other albedo measurement locations. Additionally, the uncertainty calculation is included in the dataset.

opencc-by-4.0Jan 2023View details →

Traumatic events, post-traumatic stress disorder, and proxy measures for central sensitization in chronic pain patients of a German university outpatient pain clinic

This dataset was acquired at Hannover Medical School, Hannover, Germany. The study complied with the Declaration of Helsinki, and was approved by the local ethics committee. All subjects gave written informed consent, and consent to use their data anonymously for research purposes. The study was registered at ClinicalTrials.gov (NCT05190367). Between February 2019 and July 2020, 914 patients who visited our outpatient pain department gave written consent to use their routinely collected data anonymously for research purposes. Participants were divided into four groups depending on their trauma severity: (1) no trauma; (2) accidental trauma (e.g. illness, accident, natural disaster); (3) interpersonal trauma (e.g. assault, rape, war); (4) PTSD (diagnosed according to ICD-10). Patients fulfilling two or more categories were assigned to the highest group. Data were collected using the SymptomMapper application [1]. Participants provided information about their traumas, current pain intensity (visual analogue scale, VAS (0-100) [2]), mean and maximal pain in the last 4 weeks (VAS (0-100)), sleep impairment (VAS (0-100)), acceptable pain (VAS (0-100)), pain disability index (PDI [3]), pain area (digital drawings), pain widespreadness (widespread pain index, WPI [4], derived from drawings), stress (patient health questionnaire, German version, PHQ-D [5]), anxiety (PHQ-D), depression (PHQ-D), and somatization symptoms (PHQ-D). This dataset contains the raw data as well as necessary scripts for reproducing the results of this study.   References ########## [1] Neubert TA, Dusch M, Karst M, Beissner F. Designing a Tablet-Based Software App for Mapping Bodily Symptoms: Usability Evaluation and Reproducibility Analysis. JMIR Mhealth Uhealth 2018;6(5):e127. [2] Dworkin RH, Turk DC, Farrar JT et al. Core outcome measures for chronic pain clinical trials: IMMPACT recommendations. Pain 2005;113(1):9-19. [3] Pollard CA. Preliminary Validity Study of the Pain Disability Index. Percept Mot Skills 1984;59(3): 974. [4] Wolfe F, Clauw DJ, Fitzcharles MA et al. The American College of Rheumatology Preliminary Diagnostic Criteria for Fibromyalgia and Measurement of Symptom Severity. Arthritis Care Res 2010;62(5):600-10. [5] Löwe B, Spitzer RL, Zipfel S, Herzog W. Gesundheitsfragebogen für Patienten (PHQ-D). Manual und Testunterlagen (second edition). Pfizer 2002.

dryad36/100

Data from: Predicting and measuring decision rules for social recognition in a Neotropical frog

Many animals use signals to recognize familiar individuals but risk mistakes because the signal properties of different individuals often overlap. Further, outcomes of correct and incorrect decisions yield different fitness payoffs, and animals incur these payoffs at different frequencies depending on interaction rates. To understand how signal variation, payoffs, and interaction rates shape recognition decision rules, we studied male golden rocket frogs, which recognize the calls of territory neighbors and are less aggressive to neighbors than to strangers. We first quantified patterns of individual variation in call properties and predicted optimal discrimination thresholds using signal variation. We then measured thresholds for discriminating between neighbors and strangers using a habituation-discrimination field playback experiment. Territorial males discriminated between calls differing by 9% to 12% in temporal properties, slightly higher than the predicted thresholds (5-10%). Finally, we used a signal detection theory model to explore payoff and interaction rate parameters and found that the empirical threshold matched those predicted under ecologically realistic assumptions of infrequent encounters with strangers and relatively costly missed detections of strangers. We demonstrate that receivers group continuous variation in vocalizations into discrete social categories and that signal detection theory can be applied to understand evolved decision rules.

opencc-zeroDec 2022View details →