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Text-fig. 3. Eastern wall of Jirásek's Quarry with studied section, with light-grey Acanthopyge Limestones in lower half of the wall, the UDI (in brown) in upper half followed by bioclastic breccia (Bed 46 sensu Hladil 1993) near the edge of the wall (a) and detail of UDI and adjacent limestones with the most productive beds (b). Photo January, 2019. in Rhynchonelliform Brachiopods And Trilobites Of The 'Upper Dark Interval' In The Koněprusy Area Devonian, Eifelian, Kačák Event; The Czech Republic
Text-fig. 3. Eastern wall of Jirásek's Quarry with studied section, with light-grey Acanthopyge Limestones in lower half of the wall, the UDI (in brown) in upper half followed by bioclastic breccia (Bed 46 sensu Hladil 1993) near the edge of the wall (a) and detail of UDI and adjacent limestones with the most productive beds (b). Photo January, 2019.
Text-fig. 2. Studied section in Jirásek's Quarry with essential data on lithology and samples studied on rhynchonelliform brachiopods and trilobites (black dots – productive, white dots – barren). in Rhynchonelliform Brachiopods And Trilobites Of The 'Upper Dark Interval' In The Koněprusy Area Devonian, Eifelian, Kačák Event; The Czech Republic
Text-fig. 2. Studied section in Jirásek's Quarry with essential data on lithology and samples studied on rhynchonelliform brachiopods and trilobites (black dots – productive, white dots – barren).
Fig. 4 in A new dark-saddled species of Hypostomus (Siluriformes: Loricariidae) from the upper rio Paraguay basin
Fig. 4. Lateral view of Hypostomus latifrons, NUP 2274: a) young specimen, 42.2 mm SL; b) large specimen, 200.4 mm SL.
Fig. 3 in A new dark-saddled species of Hypostomus (Siluriformes: Loricariidae) from the upper rio Paraguay basin
Fig. 3. Hypostomus peckoltoides, paratype, ZSM 39427, 90.3 mm SL. Photographed alive by Andre Werner.
Fig. 2 in A new dark-saddled species of Hypostomus (Siluriformes: Loricariidae) from the upper rio Paraguay basin
Fig. 2. Hypostomus peckoltoides, holotype, MZUSP 105226, 110.7 mm SL, from the rio Cuiabá, upper rio Paraguai basin, Mato Grosso State, Brazil.
The LSST Dark Energy Science Collaboration (DESC) Science Requirements Document v1 Released Data Products
<p>This tarball includes software and data products associated with the DESC Science Requirements Document (SRD) v1. See the "Executive Summary and User Guide" in the enclosed PDF of the DESC SRD for instructions on how to use and cite those products. The DESC SRD is described on <a href="https://arxiv.org/abs/1809.01669">arXiv</a> as follows:</p> <p>The Large Synoptic Survey Telescope (LSST) Dark Energy Science Collaboration (DESC) will use five cosmological probes: galaxy clusters, large scale structure, supernovae, strong lensing, and weak lensing. The Science Requirements Document (SRD) quantifies the expected dark energy constraining power of these probes individually and together, with conservative assumptions about analysis methodology and follow-up observational resources based on our current understanding and the expected evolution within the field in the coming years. We then define requirements on analysis pipelines that will enable us to achieve our goal of carrying out a dark energy analysis consistent with the Dark Energy Task Force definition of a Stage IV dark energy experiment.</p>
Dark Photon Exclusions from Existing Axion Haloscope Measurements
<p>Dark photon exclusions for polarized and unpolarized dark photons converted from axion measurements are each in a .mat file.</p> <p>Keys for the data are 'RBF_ueV', 'RBF_chi', 'UF_ueV', 'UF_chi', 'HAYSTAC_ueV', 'HAYSTAC_chi', 'ADMX_ueV', 'ADMX_chi', 'CAPP_ueV', and 'CAPP_chi' to obtain exclusions for dark photons for each of these experiments in the polarized and unpolarized cases. Each case has its own .mat file.</p> <p>The .py file is the Python code used to calculate cos<sup>2</sup>(theta), the square of the dot product between the dark photon polarization and the axis of the haloscope cavity in the slowly varying polarized case described in <a href="https://arxiv.org/abs/2104.09334">the associated manuscript</a>. The code shows how to calculate cos<sup>2</sup>(theta) using probability, taking the rotation of the earth into account for longer measurements. (If your computer is slow, you can use the find and replace function in your IDE to change all 'block=True' statements to 'block=False' and also change num_pts=50 instead of 500.)</p> <p>To use the .mat file format in Python, use a script like the following:</p> <pre>import matplotlib.pyplot as plt from scipy.io import loadmat mat_file = loadmat('haloscope_exclusions_unpolarized.mat') masses_in_ueV = mat_file['HAYSTAC_ueV'][0] chi_exclusion = mat_file['HAYSTAC_chi'][0] plt.figure() plt.semilogy(masses_in_ueV, chi_exclusion) plt.xlabel('Mass ($\mu$eV)') plt.ylabel('$\chi$') plt.title('HAYSTAC unpolarized dark photon exclusions') plt.show() </pre>
Wheel Out the Digital Dark Age Klaxon!
<p>Wheel Out the Digital Dark Age Klaxon, performed by the Digital Dark Age Crew.</p> <p>Written and produced by Marinus Nullbyte for the Digital Dark Age Crew, on the occasion of World Digital Preservation Day 2022. Executive producer: Johan van der Knijff.</p> <p>More information about this release, and about the Digital Dark Age Crew is available at:</p> <p><a href="https://www.bitsgalore.org/2022/11/03/wheel-out-the-digital-dark-age-klaxon">https://www.bitsgalore.org/2022/11/03/wheel-out-the-digital-dark-age-klaxon</a></p> <p>Vocals by the artificial voice of Alan Pope, which was channeled to the Digital Dark Age Crew through the mimic3 text to speech engine by Mycroft AI:</p> <p><a href="https://github.com/MycroftAI/mimic3">https://github.com/MycroftAI/mimic3</a></p> <p>All icons in the video were licensed from the Noun Project:</p> <p><a href="https://thenounproject.com/">https://thenounproject.com/</a></p> <p>Except the Myspace icon, which is public domain.</p>
Text-fig. 6. Scanning electron microscope (SEM, a, g, h) and synchrotron radiation X-ray tomographic microscopy (SRXTM, b–f) images of fruits and pollen grains of Canrightiopsis crassitesta (a–c, g, h) and fruit of Canrightiopsis intermedia (d–f); Catefica locality, Portugal. a) Dorsal view of fruit showing rim of hypanthium (arrowheads); b) Surface rendering of longitudinal section in the median plane of fruit (cut between orthoslices yz0440-0510) showing the thin fruit wall, thick endotesta of the seed coat (en, dark blue) and the orthotropous, pendent seed with the chalaza (ch) near the fruit apex and the micropyle (mi) at the fruit base; note the tiny embryo (emb) adjacent to the micropyle at the base of the fruit; c) Longitudinal section (orthoslice xz0511) through the seed wall showing the thick, finely crystalliferous endotesta (en) surrounding the nutritive tissue of the seed; d) Surface rendering of fruit in dorsal view showing rim of the hypanthium (arrowheads) and apical stigmatic region (st); e) Surface rendering of longitudinal section of fruit in (d) (cut at orthoslice xz0560) showing the crystalliferous endotesta (en, dark blue) and the inner tissues of the seed; f) Longitudinal section (orthoslice xz0560) through fruit and seed showing the finely crystalliferous endotesta (en) and thin fruit wall (fr); g, h) Pollen grains from apical region of fruit showing poorly defined margin of the single colpus, reticulate tectum and muri ornamented by minute verrucae. Specimens, Catefica 343-S174311 (a), Catefica 49-S174159 (b, c), Catefica 50-S174905 (d–f), Catefica 342-S122089 (g, h). Scale bars = 300 Μm (a, b, d, e), 150 Μm (c, f), 6 Μm (g), 3 Μm (h). g, h published with permission from Grana. in The Early Cretaceous Mesofossil Flora Of Catefica, Portugal: Angiosperms
Text-fig. 6. Scanning electron microscope (SEM, a, g, h) and synchrotron radiation X-ray tomographic microscopy (SRXTM, b–f) images of fruits and pollen grains of Canrightiopsis crassitesta (a–c, g, h) and fruit of Canrightiopsis intermedia (d–f); Catefica locality, Portugal. a) Dorsal view of fruit showing rim of hypanthium (arrowheads); b) Surface rendering of longitudinal section in the median plane of fruit (cut between orthoslices yz0440-0510) showing the thin fruit wall, thick endotesta of the seed coat (en, dark blue) and the orthotropous, pendent seed with the chalaza (ch) near the fruit apex and the micropyle (mi) at the fruit base; note the tiny embryo (emb) adjacent to the micropyle at the base of the fruit; c) Longitudinal section (orthoslice xz0511) through the seed wall showing the thick, finely crystalliferous endotesta (en) surrounding the nutritive tissue of the seed; d) Surface rendering of fruit in dorsal view showing rim of the hypanthium (arrowheads) and apical stigmatic region (st); e) Surface rendering of longitudinal section of fruit in (d) (cut at orthoslice xz0560) showing the crystalliferous endotesta (en, dark blue) and the inner tissues of the seed; f) Longitudinal section (orthoslice xz0560) through fruit and seed showing the finely crystalliferous endotesta (en) and thin fruit wall (fr); g, h) Pollen grains from apical region of fruit showing poorly defined margin of the single colpus, reticulate tectum and muri ornamented by minute verrucae. Specimens, Catefica 343-S174311 (a), Catefica 49-S174159 (b, c), Catefica 50-S174905 (d–f), Catefica 342-S122089 (g, h). Scale bars = 300 Μm (a, b, d, e), 150 Μm (c, f), 6 Μm (g), 3 Μm (h). g, h published with permission from Grana.
Text-fig. 1. The Catefica exposure along the road between Catefica and Mugideira photographed in 1989 when the mesofossil flora was discovered. The exposed strata are mainly cross-bedded light colored sands, darker horizons of clay and dark lenses with mesofossils. The most productive sample, Catefica sample 49, was collected in the basal part of the exposed sequence (arrow head). One of the authors (PRC) exploring the middle part of the section. Photo K. R. Pedersen. in The Early Cretaceous Mesofossil Flora Of Catefica, Portugal: Angiosperms
Text-fig. 1. The Catefica exposure along the road between Catefica and Mugideira photographed in 1989 when the mesofossil flora was discovered. The exposed strata are mainly cross-bedded light colored sands, darker horizons of clay and dark lenses with mesofossils. The most productive sample, Catefica sample 49, was collected in the basal part of the exposed sequence (arrow head). One of the authors (PRC) exploring the middle part of the section. Photo K. R. Pedersen.
Figs 7–15 in A revision of the endemic South African dark sac spider genus Austrophaea (Araneae: Corinnidae)
Figs 7–15. Austrophaea zebra: (7–13) male (Kei Mouth): (7, 8) palp, ventral and retrolateral views; (9–13) schematic representation of male palpal retrolateral tibial apophysis in ventral (9), retrolateral ventral (10), retrolateral (11), retrolateral dorsal (12), and dorsal views (13); (14, 15) female (Port Edward): (14) epigyne, ventral view, (15) vulva, dorsal view. Abbreviations: CD – coiled sperm duct; EM – embolus; MA – median apophysis; SS – spermathecal socket; SP 1 – spermatheca 1; SP 2 – spermatheca 2. Scale bars = 0.25 mm.
Figs 1–6 in A revision of the endemic South African dark sac spider genus Austrophaea (Araneae: Corinnidae)
Figs 1–6. Austrophaea zebra Lawrence: (1–3) male: (1) general habitus, (2) morphology of leg I, (3) lateral view; (4–6) female: (4) general habitus, (5) morphology of leg I, (6) lateral view. Scale bars = 2.5 mm.
Dark Halo Craters Data
<p>This dataset is a global collection of the longitude and latitude and diameters of dark halo craters. The software used to map the DHCs was Lunar QuickMap.The data for the iron content of the ejecta was found both from the Kaguya (Selene) and Clementine missions. We mapped all longitudes and latitudes of the lunar surface.</p> <p>We determined a crater to be a DHC if it had an ejecta pattern with visibly higher iron content than the surrounding rock. All of the counted DHCs exhibited this quality. We omitted craters that had elevated iron inside the crater rim (as opposed to in the ejecta) because the iron signature inside might result from visible mare that filled in the crater subsequent to impact. Areas associated with visible lunar maria were ignored for this particular data set.</p> <p>We identified and mapped craters globally that had a minimum diameter of 1 km. We mapped the section 40–70 W, 20–70 S with no minimum diameter limit. Determining whether the ejecta had an iron content pattern that is significantly different and distinctive from the surrounding rock is subjective, so we mapped craters conservatively. The surface was mapped by two different people so there could be some additional human error and slight subjectivity of DHCs. We only considered craters with a clearly identifiable ejecta pattern, and we required that the ejecta had to surround at least 25% of the crater. We allowed cases with asymmetrical ejecta.</p> <p>We mapped the craters in 10-degree longitude bands, first checking the iron content and ejecta pattern of craters and then confirmed the DHC with albedo satellite images. We took the longitude and latitude of the center of the crater and measured the diameter with QuickMap tools, from one rim to the other rim.<br> </p>
Figs 15–17 in Vendaphaea, a new dark sac spider genus apparently endemic to the Soutpansberg Mountains, South Africa (Araneae: Corinnidae)
Figs 15–17. Scanning electron micrographs of V. lajuma sp. n. ^spinnerets: (15) ALS, (16) PMS, (17) PLS. Abbreviations: Ac – aciniform gland spigot, Cy – cylindrical gland spigot, miAMP – minor ampullate gland spigot, Pi – piriform gland spigot.
Figs 22–27 in Vendaphaea, a new dark sac spider genus apparently endemic to the Soutpansberg Mountains, South Africa (Araneae: Corinnidae)
Figs 22–27. Vendaphaea lajuma sp. n., male (22–25) and female (26, 27) genitalia: (22) left palp, prolateral view; (23) same, ventral view; (24) same, retrolateral view; (25) same, dorsal view; (26) epigyne, ventral view; (27) same, dorsal view. Scale bars = 0.25 mm.
Figs 18–21 in Vendaphaea, a new dark sac spider genus apparently endemic to the Soutpansberg Mountains, South Africa (Araneae: Corinnidae)
Figs 18–21. Scanning electron micrographs of Vendaphaea lajuma sp. n. genitalia: (18) male palp, dorsal view; (19) cymbial setae, enlarged; (20) male palpal tegulum, ventral view; (21) female epigyne, ventral view. Abbreviations: CD – conductor, CO – copulatory opening, CS – clavate cymbial setae, DL – dorsal lobe of palpal tibia, DSM – dorsal setal mat, EM – embolus, EP – epigynal plug, MA – median apophysis, MS – median septum, PCR – proximal cymbial ridge, SS – setal mat setae, TA – tibial apophysis.
Galactic Diffuse Emission Spectrum between 0.5 and 8.0 MeV and between 30 keV and 8 MeV for the search of PBH and Light Dark Matter
<p>Spectra and response files of the soft gamma-ray spectrum from Inverse Compton scattering in the Milky Way between 0.5 and 8.0 MeV, measured with INTEGRAL/SPI. The fluxes have been extracted with spimodfit assuming GALPROP v56 models according to Voyager 1, AMS-02, and Fermi/LAT data, plus different variants to change the interstellar radiation field, the diffusion properties, or the cosmic-ray halo size (<a href="https://ui.adsabs.harvard.edu/abs/2022A%26A...660A.130S/abstract">Siegert et al., 2022</a>). The respective galdef files are included. In particular:</p> <ul> <li>voyager: propagation model of Bisschoff et al. (2019), Table 2</li> <li>voyager_Dg10001: <span class="math-tex">\(\delta_1 = 0\)</span></li> <li>voyager_Dg1Dg205: <span class="math-tex">\(\delta_1 = \delta_2 = 0.5\)</span></li> <li>voyager_ISRFopt10: factor 10 stronger optical ISFR</li> <li>voyager_z8kpc_KL: thick halo with 8 kpc half-thickness</li> </ul> <p>In addition, there are spectra from 30 keV to 8 MeV (spec_0030-8000keV_<name>.fits, <a href="https://ui.adsabs.harvard.edu/abs/2022PhRvD.106b3030B/abstract">Berteaud et al., 2022</a>), separated into:</p> <ul> <li>CV: spectrum of unresolved point sources in the Galactic plane, mostly cataclysmic variables (strong systematics)</li> <li>IC: spectrum of Inverse Compton scattering of cosmic ray GeV electrons (see above)</li> <li>positronium: spectrum of positronium decay (annihilation of electrons with positrons after intermediate bound state)</li> <li>NFW: spectrum of dark matter contributions that would follow a Navarro Frenk White density profile (mostly consistent with zero)</li> <li>total: spectrum of the above combined</li> </ul> <p>The notebooks for dark matter related bounds when using this data as well as auxiliary files to create the templates are given as (<a href="https://ui.adsabs.harvard.edu/abs/2022PhRvD.106b3030B/abstract">Berteaud et al., 2022</a>, <a href="https://ui.adsabs.harvard.edu/abs/2023MNRAS.520.4167C/abstract">Calore et al., 2023</a>):</p> <ul> <li>DM_fsr.ipynb: Notebook for final state radiation bounds</li> <li>DM_fsr.py: astromodels function for final state radiation spectrum</li> <li>DM_2gamma.ipynb: Notebook for gamma gamma final state bounds</li> <li>DM_2gamma.py: astromodels function for gamma gamma spectrum</li> <li>Positronium_Spectrum.py: astromodels function for Positonium spectrum</li> <li>DM_pbh.py: script for obtaining PBH bounds</li> <li>diff_@@.csv: spectra for PBH evaporation</li> <li>total_spectrum.fits.gz: total Galactic spectrum</li> <li>NFW_spectrum.fits.gz: NFW-only spectrum</li> </ul>
Data and software: 'Survey Operations for the Dark Energy Spectroscopic Instrument'
<p>Supplementary material to the DESI publication "Survey Operations for the Dark Energy Spectroscopic Instrument".</p><p>The main "figures.py" script generates the figures in the paper from the included data files. The software relies on the DESI software stack available at github.com/desihub, and conveniently available at NERSC in the default DESI environment.</p><p>Some documentation on the code implementing the survey and for running the survey simulations is available here:</p><ul><li>https://desisurvey.readthedocs.io/en/latest/</li><li>https://surveysim.readthedocs.io/en/latest/</li></ul><p>Contents:</p><ul><li>Configuration files<ul><li>config-main-actual.yaml: a yaml file giving the configuration for the survey simulation software (https://github.com/desihub/surveysim/releases/tag/0.12.5), specifying things like interexposure times and downtime, using the actual long shutdowns we had.</li><li>config-main-nominal.yaml: a yaml file giving the configuration for the survey simulation software, using the nominal long shutdowns we planned for.</li><li>config-main.yaml: same as config-main-nominal.yaml, except with the default name looked for by the survey simulation software.</li><li>rules-main.yaml: configuration rules file controlling how the next tile selector selects files for observation, implementing our depth-first strategy.</li></ul></li><li>Software files<ul><li>figures.py: main routines for generating the plots in this publication. Running `python figures.py` will create all of the figures used in this paper.</li><li>precess.py: set of routines implementing the precession of the Earth's pole used by figures.py for accurate airmass calculations.</li><li>downtime.py: routines used by figures.py for computing statistics about DESI's time usage, in particular the downtime.</li><li>util_efs.py: utility routines, primarily for making plots used by figures.py</li><li>util_efs_c.pyx: cython routines used by util_efs.py</li><li>margincomputations.py: routines for computing survey margin; i.e., how well we did relative to how much time was available.</li></ul></li><li>Data files<ul><li>Survey<ul><li>exposures-daily-main-20220614.ecsv: list of main survey exposures taken through 2022-06-14, following processing by the offline pipeline.</li><li>exposures-20220614.ecsv: list of main survey exposures taken through 2022-06-14, before processing by the offline pipeline. This largely duplicates exposures-daily, but contains much less information and contains more records for rare cases when exposures cannot be processed by the offline pipeline.</li><li>tiles-4112-packing-20210405-decorated-fixed.fits: file giving the geometry of DESI tile centers on the sky, plus associated information, like the extinction and stellar density at those locations.</li><li>tiles-daily.csv</li></ul></li><li>Simulation<ul><li>ephem_2019-01-01_2027-12-31.fits: ephemerides for DESI site for 2019 through 2027, generated by the desisurvey software ephemerides module. https://github.com/desihub/desisurvey</li><li>desi-status-end-nominal.ecsv: tile file giving completion of each DESI tile, for a survey simulation using the nominal configuration file.</li><li>desi-status-end-actual-noslew.ecsv: tile file giving completion of each DESI tile, for a survey simulation using the actual configuration file, without slew optimization</li><li>desi-status-end-actual.ecsv: tile file giving the completion of each DESI tile, for a survey simulation using the actual configuration file.</li><li>exposures_actual-noslew.fits: exposures generated by survey simulation software using the 'actual' configuration, with slew optimization disabled.</li><li>exposures_actual.fits: exposures file generated by survey simulation software using the 'actual' configuration.</li><li>exposures_nominal.fits: exposures file generated by survey simulation software using the 'nominal' configuration.</li><li>stats_actual.fits: statistics file generated by survey simulation software using the 'actual' configuration, containing information about DESI time usage.</li><li>stats_actual-noslew.fits: same as stats_actual.fits, except with slew time optimization disabled.</li><li>stats_nominal.fits: same as stats_actual.fits, except with the nominal survey sim configuration file.</li><li>tiles-daily.csv: tile file with detailed information on all tiles completed by the survey</li><li>tiles-main-20220614.ecsv: tile file with tile completeness information on 20220614</li><li>tiles-main.ecsv: tile file with completeness information on tiles in the survey</li><li>performance_current.csv.gz: performance information detailing state of DESI instrument every second, used for tracking downtime statistics.</li></ul></li></ul></li></ul><p>Dependencies: The included software uses the 'surveysim,' 'desisurvey,' and 'desimodel' packages, available on github through the desihub organization. Otherwise it depends on the usual astronomy software stack: numpy scipy matplotlib astropy. Alternatively, people with access to NERSC can load the default DESI environment and pull in all needed dependencies.</p>
Figure 16 in Unusual Dark Forms of the Solanum Fruit Fly Bactrocera latifrons (Hendel) in Hawaii (Tephritidae: Dacini)
Figure 16. Lateral views showing the difference in the width of the mesopleural stripe. A. Bactrocera latifrons ex USDA fruit fly lab, Honolulu, Hawaii. B. Holotype of B. citima, Chiangdao, Chiangmai prov., Thailand.
Figures 1–15 in Unusual Dark Forms of the Solanum Fruit Fly Bactrocera latifrons (Hendel) in Hawaii (Tephritidae: Dacini)
Figures 1–15. Lateral, dorsal views and abdomen close-ups of five specimens of Hawaiian Bactrocera latifrons with varying degrees of dark markings on the abdomen and the scutum and legs. 1–3: female collected on Oahu, Kahuku, Fukuyama farm, leg. S. Graham (no date on labels), with typical 'textbook' orange-brown abdomen and absence of dark markings. 4–6: UHIM2015.04242 male collected on Maui, Kula, Howard Harada coffee, 26.vii–4.viii-06. leg. L. Leblanc. 7–9: female collected on Oahu, 2017, leg. S. Graham. 10–12: UHIM2015.04243 collected on Maui, Kula, Flora Umeno's coffee plot, 16–23.vi.06, leg. L. Leblanc. 13–15: UHIM2016.25466 female collected on Oahu, Ala Wai, garden, 5.ii.90 ex wild tomatoes, leg. M. M. Ramadan.
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.