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Fig. 7 in New marine Thinophilus species (Diptera: Dolichopodidae: Hydrophorinae) from the Thai Andaman Sea coast and new records from peninsular Thailand
Fig. 7. Thinophilus plektron Samoh & Grootaert sp. nov. Male terminalia (Abdulloh Samoh leg., PSUNHM (PSUZCDIP0013)). A. Ventral view of tips of surtstyli. B. Dorsal view of tip of fused cerci. C. Ventral view of epandrium. D. Lateral view on epandrium. Scale = 1 mm.
Fig. 5 in New marine Thinophilus species (Diptera: Dolichopodidae: Hydrophorinae) from the Thai Andaman Sea coast and new records from peninsular Thailand
Fig. 5. Thinophilus plektron Samoh & Grootaert sp. nov. Male habitus (Abdulloh Samoh leg., PSUNHM (PSUZCDIP0013)).
Fig. 3 in New marine Thinophilus species (Diptera: Dolichopodidae: Hydrophorinae) from the Thai Andaman Sea coast and new records from peninsular Thailand
Fig. 3. Thinophilus inaequalis Samoh & Grootaert sp. nov. Female habitus (Abdulloh Samoh leg., PSUNHM (PSUZCDIP0012)).
Fig. 4 in New marine Thinophilus species (Diptera: Dolichopodidae: Hydrophorinae) from the Thai Andaman Sea coast and new records from peninsular Thailand
Fig. 4. Thinophilus inaequalis Samoh & Grootaert sp. nov. Male terminalia (Abdulloh Samoh leg., PSUNHM (PSUZCDIP0011)). A. Ventral view on epandrium. B. Tip of right surstylus. C. Lateral view on left side of epandrium with a pointed left surstylus. D. Dorsal view on cerci. Scale = 0.1 mm.
Fig. 1 in New marine Thinophilus species (Diptera: Dolichopodidae: Hydrophorinae) from the Thai Andaman Sea coast and new records from peninsular Thailand
Fig. 1. Map of peninsular Thailand which is bordered by the Gulf of Thailand, a part of the South China Sea in the East and the Andaman Sea (Indian Ocean) in the West. The provenance of the three new species is indicated.
Fig. 2 in New marine Thinophilus species (Diptera: Dolichopodidae: Hydrophorinae) from the Thai Andaman Sea coast and new records from peninsular Thailand
Fig. 2. Thinophilus inaequalis Samoh & Grootaert sp. nov. Male habitus (Abdulloh Samoh leg., PSUNHM (PSUZCDIP0011)).
Fig 5 in Publishing trends and productivity in insect taxonomy from 1946 through 2012 based on an analysis of the Zoological Record for four species-rich families
Fig 5 (continued from previous page). Number of articles published by continent (Europe, North America, South America, Africa, Asia and Australia) between 1946 and 2012. A. Cicadellidae. B. Miridae. C. Pyralidae. D. Staphylinidae.
Fig. 3 in A review of Dendrocephalus (Dendrocephalinus) (Crustacea: Anostraca) with the first records of male-male anostracan aggressive competition
Fig. 3. Dendrocephalus proeliator sp. nov, male-male aggressive interactions. A. Encounter. B. Circling. C. Head to head attack. D. Broadside attack. E–F. Chasing.
Fig. 2 in A review of Dendrocephalus (Dendrocephalinus) (Crustacea: Anostraca) with the first records of male-male anostracan aggressive competition
Fig. 2. Dendrocephalus proeliator sp. nov. Paratypes; Florida, Dade County; FLMNH Type 9041. A. Male head, anterior view. B. Female, right lateral view. C. Right limb V, anterior view. D. Two examples of the egg. Abbreviations: 1V = first ventral branch; 2A = apical branch; 2D = dorsal branch (terminology follows Pereira 1983). Scale bar: A = 2 mm; B = 7 mm; C = 1 mm; D = 1.5 mm.
Fig. 1. Dendrocephalus spec. A in A review of Dendrocephalus (Dendrocephalinus) (Crustacea: Anostraca) with the first records of male-male anostracan aggressive competition
Fig. 1. Dendrocephalus spec. A. Dendrocephalus acacioidea, male head, left side, anterior view. B. Dendrocephalus alachua, male head, left side, anterior view. C. Dendrocephalus lithacus, male head, left side, anterior view. D. Dendrocephalus acacioidea, brood pouch, right, lateral view. E. Dendrocephalus alachua, brood pouch, right, lateral view. F. Dendrocephalus lithacus, brood pouch, right, lateral view. G. Dendrocephalus lithacus, male, labrum, ventral view. H. Dendrocephalus lithacus, gonopods, right, lateral view. Scale bar: A–C = 1 mm; D–F, H = 4 mm; G = 0.25 mm.
Fig. 2 in Three new generic records and descriptions of four new species of jumping spiders (Araneae, Salticidae) from Sri Lanka
Fig. 2. Live specimens of Bristowia Reimoser, 1934 and Habrocestum Simon, 1876. A–B. B. gandhii sp. nov., ♀ from IFS Arboretum, Dambulla (IFS_SAL 543). C–D. H. kodigalaensis sp. nov., Ƌ from Ritigala SNR, Kodigala, Sri Lanka (IFS_SAL 516).
Fig. 10 in Three new generic records and descriptions of four new species of jumping spiders (Araneae, Salticidae) from Sri Lanka
Fig. 10. Macaroeris nidicolens (Walckenaer, 1802). A. Ƌ, habitus, dorsal view. B, D. Palp, ventral view. C, E. Palp, retrolateral view. Abbreviations: CY = cymbium; CYD = cymbial depression; E = embolus; EB = embolic base; RTA = retrolateral tibial apophysis SD = sperm duct; T = tegulum. Scale bars: A = 1 mm; B–E = 0.2 mm.
Fig. 7 in Three new generic records and descriptions of four new species of jumping spiders (Araneae, Salticidae) from Sri Lanka
Fig. 7. Habrocestum kodigalaensis sp. nov. A. Habitus, Ƌ from Ritigala SNR, Kodigala, dorsal view (IFS_SAL 516). B. Habitus, Ƌ from Riverston, Knuckles, dorsal view (IFS_SAL 345). C. Habitus, ♀ from Ritigala SNR, Kodigala, dorsal view (IFS_SAL 467). D. Male palp, ventral view. E. Male palp, retrolateral view. F. Female epigynum, ventral view. Abbreviations: E = embolus; MW = membranous window; SD = sperm duct; T = tegulum; PLT = proximal lobe of tegulum; RTA = retrolateral tibial apophysis; VR = vaginal roof. Scale bars: A–C = 1 mm; D–F = 0.2 mm.
Fig. 5 in Three new generic records and descriptions of four new species of jumping spiders (Araneae, Salticidae) from Sri Lanka
Fig. 5. Habrocestum hantaneensis sp. nov. A, C–D. Ƌ (IFS_SAL 350). B, E–F. ♀ (IFS_SAL 456). A.–B. Habitus, dorsal view. C. Palp, ventral view. D. Palp, retrolateral view. E. Epigynum, ventral view. F. Vulva, ventral view. Abbreviations: AG = accessory gland; E = embolus; EB = embolic base; FD = fertilization duct; MW = membranous window; PLT = proximal lobe of tegulum; RTA = retrolateral tibial apophysis; S = spermathecae; SD = sperm duct; VR = vaginal roof. Scale bars: A–B = 1 mm; C–F = 0.2 mm.
In-situ data recorded from thaumatin crystals on Diamond Light Source VMXi
<p>Data collected as part of routine beamline commissioning, from samples of thaumatin grown in 0.1 M Sodium citrate, 0.75M Sodium / Potassium tartrate. Data were collected in unattended mode with positions identified <em>via</em> SynchWeb from photographs taken with a Formulatrix imaging system (picture included.) Each data set consists of 200 images taken with an Eiger 2X 4M detector at a distance of 186mm, with exposure time of 2 ms, wavelength 0.97950 angstroms and 2% transmission with a DMM beam. Automated processing combined data using the xia2 multiplex tool to give a sufficiently complete data set for structure solution and refinement.</p>
Mobile Device Voice Recordings at King's College London (MDVR-KCL) from both early and advanced Parkinson's disease patients and healthy controls
<p><strong>Dataset description</strong></p> <p>The dataset description will start with describing the local conditions and other metadata, then will continue with describing the recording procedure and annotation methodology. Finally, a brief description of the dataset deployment and publication will be given.</p> <p><strong>Meta Information</strong></p> <p>The dataset was recorded at King's College London (KCL) Hospital, Denmark Hill, Brixton, London SE5 9RS in the period from 26 to 29 September 2017. We used a typical examination room with about ten square meters area and a typical reverberation tome of approx. 500ms to perform the voice recordings. Due to the fact, that the voice recordings are performed in the realistic situation of doing a phone call (i.e. participant holds the phone to the preferred ear and microphone is in direct proximity to the mouth), one can assume that all recordings were performed within the reverberation radius and thus can be considered as “clean”.</p> <p><strong>Recording Procedure</strong></p> <p>We used a Motorola Moto G4 Smartphone as recording device. To perform the voice recordings on the device, we developed a “Toggle Recording App”, which uses the same functionalities as the voice recording module used within the i-PROGNOSIS Smartphone application, but deployed as a standalone android application. This means, that the voice capturing service runs as a standalone background service on the recording device and triggers voice recordings via on- and off-hook signals of the Smartphone. Due to the fact, that we directly record the microphone signal, and not the GSM (“Global System for Mobile Communications”) compressed stream, we end up with high quality recordings with a sample rate of 44.1 kHz and a bit depth of 16 Bit (audio CD quality). The raw, uncompressed data is directly written to the external storage of the Smartphone (SD-card) using the well-known WAVE file format (.wav). We used the following workflow to perform a voice recording:</p> <ul> <li>Ask the participant to relax a bit and then to make a phone call to the test executor (off-hook signal triggered).}</li> <li>Ask the participant to read out “The North Wind and the Sun”</li> <li>Depending on the constitution of the participant either ask to read out “Tech. Engin. Computer applications in geography snippet”</li> <li>Start a spontaneous dialog with the participant, the test executor starts asking random questions about places of interest, local traffic, or personal interests if acceptable.</li> <li>Test executor ends call by farewell (on-hook signal triggered).</li> </ul> <p><strong>Annotation Scheme</strong></p> <p>For each HC and PD participant, we labeled the data regarding scores on the Hoehn & Yahr (H&Y), as well as the UPDRS II part 5 and UPDRS III part 18 scale. The voice recordings are labeled in the following scheme:</p> <p>SI_ HS_ HYR_ UPDRS II-5_UPDRS III-18</p> <p>with</p> <ul> <li>SI as subject identification in the form ID<em>NN</em>, <em>N</em> in [0, 9]</li> <li>HS as the health status label (hc or pd accordingly)</li> <li>HYR as the expert assessed H&Y scale rating</li> <li>UPDRS II-5 as the according expert peer-reviewed score</li> <li>UPDRS III-18 as the according expert assessed score</li> </ul> <p>For example, an audio recording with the file name “ID02_pd_1_2_1.wav” represents a recording of the third participant (First participant was anonymized as ID00), which has PD and a H&Y rating of 1, a UPDRS II-5 score of 2 and a UPDRS III-18 score of 1. At this point, it should be noted, that also all healthy controls were evaluated with regard to the introduced scales, because Parkinson's disease and voice degradation correlate, but don't match exactly. This means, that the data set includes one HC participant (ID31) with UPDRS II-5 and III-18 rating of 1, and also includes PD patients with UPDRS II-5 and III-18 ratings of 0. It should be emphasized, that this does not mean the data set includes ambiguous information, but that an expert was not able to hear voice degradation that would end up in a UPDRS rating greater than zero. Machine learning approaches may be able to nevertheless classify correctly, or at least learn to correlate, but not match PD and voice degradation at any time.</p> <p><strong>Appendix</strong></p> <p>North Wind and the Sun (Orthographic Version):</p> <p>“The North Wind and the Sun were disputing which was the stronger, when a traveler came along wrapped in a warm cloak. They agreed that the one who first succeeded in making the traveler take his cloak off should be considered stronger than the other. Then the North Wind blew as hard as he could, but the more he blew the more closely did the traveler fold his cloak around him; and at last the North Wind gave up the attempt. Then the Sun shone out warmly, and immediately the traveler took off his cloak. And so the North Wind was obliged to confess that the Sun was the stronger of the two.”</p> <p>BNC – Tech. Engin. Computer applications in geography snippet:</p> <p>“[...] This is because there is less scattering of blue light as the atmospheric path length and consequently the degree of scattering of the incoming radiation is reduced. For the same reason, the sun appears to be whiter and less orange-coloured as the observer's altitude increases; this is because a greater proportion of the sunlight comes directly to the observer's eye. Figure 5.7 is a schematic representation of the path of electromagnetic energy in the visible spectrum as it travels from the sun to the Earth and back again towards a sensor mounted on an orbiting satellite. The paths of waves representing energy prone to scattering (that is, the shorter wavelengths) as it travels from sun to Earth are shown. To the sensor it appears that all the energy has been reflected from point P on the ground whereas, in fact, it has not, because some has been scattered within the atmosphere and has never reached the ground at all. [...]”</p>
RF recordings of GPS SVN49 broadcasting non-standard codes
<p>This dataset consists of several recordings of the L1 signal broadcasted by GPS<br> SVN49 between 2019-06-26 and 2019-06-28. This satellite broadcasts a<br> non-standard code as its L1 C/A signal, where the usual spread-spectrum PRN is<br> replaced by a PRN which consists of alternating zeros and ones (akin to a square<br> wave subcarrier). This produces strong spectral lines at +/-511.5kHz from the L1<br> centre frequency.</p> <p>The signal is modulated with a navigation message in the usual way using 50baud<br> BPSK.</p> <p>The recordings have been made with a LimeSDR using an external 10MHz GPSDO and a<br> small and inexpensive GPS patch antenna.</p> <p><strong>Included files</strong></p> <p>The .bin files contain waterfall data generated with STRF. This<br> data can be used to identify the satellite producing the signal using Doppler<br> measurements.</p> <p>The mjd58660.dat file contains Doppler measurements extracted with STRF.</p> <p>The .c64 files are IQ recordings of the upper sideband of<br> the modulation (centred at L1 + 511.5kHz). One of them is done at 5ksps and<br> another at 10ksps. The timestamp of the start of each recording is indicated in<br> the filename. The format is complex IQ data as 32-bit floats.</p>
Fig. 4 in Description of a new genus and species of Chrysopetalidae (Annelida: Polychaeta) from the NE Atlantic, with some further records of related species
Fig. 4. Craseoschema thyasiricola gen. et sp. nov. Stereo (A–C) and compound (D–E) microscope images. A. Prostomium, dorsal view. B. Median region, dorsal view. C. Pygidium, ventral view. D. Neuroacicula of a median parapodium. E. Neurochaetae of a median parapodium.
Fig. 3 in Description of a new genus and species of Chrysopetalidae (Annelida: Polychaeta) from the NE Atlantic, with some further records of related species
Fig. 3. Craseoschema thyasiricola gen. et sp. nov. Line drawings. A. Anterior end, dorsal view. B. Prostomium, ventral view. C. Third parapodium, posterior view. D. Median parapodium, posterior view. E. Notochaeta from median parapodium. F. Ventralmost neurochaeta from the second parapodium. G. Dorsalmost neurochaeta from median parapodium.
Fig. 5 in Description of a new genus and species of Chrysopetalidae (Annelida: Polychaeta) from the NE Atlantic, with some further records of related species
Fig. 5. Craseoschema thyasiricola gen. et sp. nov. SEM images. A. Fragment from median region, posterior view. B. Median parapodium, posterior view. C. Notochaetae of median parapodium. D. Notochaetal tips. E–F. Dorsalmost neurochaetae. G–H. Ventralmost neurochaetae.
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.