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Fig 5 from: Srygley RB, Senior LB (2024) Illustrated review of Mormon cricket Anabrus simplex (Tettigoniidae, Tettigoniinae) embryonic development. Journal of Orthoptera Research 33(1): 87-93. https://doi.org/10.3897/jor.33.98763

Fig 5 Phase V: Dorsal closure A. Stage 19, ventral view; B. Stage 20, ventral view; C. Stage 21, lateral view; D. Stage 21 to 22, ventral view; Phase VI: Completion E. Stage 23, ventral view; F. Stage 23, lateral view; G. Stage 24, ventral view. Scale bars: 2 mm.

opencc-by-4.0Mar 2024View details →
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Fig 1 from: Srygley RB, Senior LB (2024) Illustrated review of Mormon cricket Anabrus simplex (Tettigoniidae, Tettigoniinae) embryonic development. Journal of Orthoptera Research 33(1): 87-93. https://doi.org/10.3897/jor.33.98763

Fig 1 Phase I: Formation and differentiation of the embryonic primordium. Images show the posterior end of the egg only: A. Stage 4; B. Stage 5; C. Stage 6; and D. Stage 6 transitioning to Stage 7. Scale bars: 2 mm.

opencc-by-4.0Mar 2024View details →
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Fig 6 from: Srygley RB, Senior LB (2024) Illustrated review of Mormon cricket Anabrus simplex (Tettigoniidae, Tettigoniinae) embryonic development. Journal of Orthoptera Research 33(1): 87-93. https://doi.org/10.3897/jor.33.98763

Fig 6 The minimum age of each embryo from day of oviposition (maximum age indicated by error bar). Embryos that were between two stages (e.g., Stage 6 to 7) were given a value half-way between the two stages (e.g., 6.5). Closed circles: embryos incubated at a daily 12:12 h cycle of 30:15°C; open circles: embryos incubated at 30:15°C for the initial 35 days and then the daily maximum and minimum temperatures were varied each week thereafter. Inset: embryos in various stages of development in week 8.

opencc-by-4.0Mar 2024View details →
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Fig 4 from: Srygley RB, Senior LB (2024) Illustrated review of Mormon cricket Anabrus simplex (Tettigoniidae, Tettigoniinae) embryonic development. Journal of Orthoptera Research 33(1): 87-93. https://doi.org/10.3897/jor.33.98763

Fig 4 Phase IV: Katatrepsis. A. Stage 15, lateral view with anterior end of embryo to the left; B. Stage 15, dorso-lateral view with chorion removed; C. Stage 16, lateral view with anterior end of embryo to the right; D. Stage 17, lateral view; E. Stage 18, ventral view showing its length relative to the whole egg. Scale bars: 2 mm.

opencc-by-4.0Mar 2024View details →
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Figure 1 from: Acquah ME, Aboagye F, Ashong Y, Mosi L (2024) Development of a field diagnostic tool for Schistosoma mansoni Praziquantel resistant markers in selected endemic communities. Research Ideas and Outcomes 10: e120899. https://doi.org/10.3897/rio.10.e120899

Figure 1 Graphical Abstract. Adapted from Summers et al. (2022), available under the terms of the Creative Commons Attribution License 4.0 (CC BY 4.0).

opencc-by-4.0Mar 2024View details →
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Research carried out on the Brazilian coast that deals with modeling sea level rise, and the methodologies applied in development.

Open the record for dataset details and reuse information.

opencc-by-4.0Mar 2024View details →
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THE NEED TO CONDUCT MARKETING RESEARCH AND DEVELOP APPROACHES IN ENTERPRISES

Open the record for dataset details and reuse information.

opencc-by-4.0Apr 2024View details →
zenodo28/100

Supplementary material 1 from: Vyshedskiy A, Mahapatra S, Dunn R (2017) Linguistically deprived children: meta-analysis of published research underlines the importance of early syntactic language use for normal brain development. Research Ideas and Outcomes 3: e20696. https://doi.org/10.3897/rio.3.e20696

Linguistic isolates performance in verbal and nonverbal tests

opencc-zeroAug 2017View details →
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Figure 5 from: Vyshedskiy A, Mahapatra S, Dunn R (2017) Linguistically deprived children: meta-analysis of published research underlines the importance of early syntactic language use for normal brain development. Research Ideas and Outcomes 3: e20696. https://doi.org/10.3897/rio.3.e20696

Figure 5 - Flexible syntax, prepositions, adjectives, verb tenses, and other common elements of grammar, all facilitate the human ability to communicate an infinite number of novel images with the use of a finite number of words. The graph shows the number of distinct images that can be transmitted with high fidelity in a communication system with 1,000 nouns as a function of the number of spatial prepositions. In a communication system with no spatial prepositions and other recursive elements, 1000 nouns can communicate 1000 images to a listener. Adding just one spatial preposition allows for the formation of three-word phrases (such as: 'a bowl behind a cup' or 'a cup behind a bowl') and increases the number of distinct images that can be communicated to a listener from 1000 to one million (1000x1x1000). Adding a second spatial preposition and allowing for five-word sentences of the form object-preposition-object-preposition-object (such as: a bowl on a cup behind a plate) increases the number of distinct images that can be communicated to four billion (1000x2x1000x2x1000). The addition of a third spatial preposition increases the number of distinct images to 27 trillion (1000x3x1000x3x1000x3x1000), and so on. In general, the number of distinct images communicated by three-word sentences of the structure object-preposition-object equals the number of object-words times the number of prepositions times the number of object-words. A typical language with 1000 nouns and 100 spatial prepositions can theoretically communicate 1000101 x 100100 distinct images. This number is significantly greater than the total number of atoms in the universe. For all practical purposes, an infinite number of distinct images can be communicated by a syntactic communication system with just 1000 words and a few prepositions. Prepositions, adjectives, and verb tenses dramatically facilitate the capacity of a syntactic communication system with a finite number of words to communicate an infinite number of distinct images. Linguists refer to this property of human languages as recursion. The "infiniteness" of human language has been explicitly recognized by "Galileo, Descartes, and the 17th-century 'philosophical grammarians' and their successors, notably von Humboldt" (Hauser et al. 2002). The infiniteness of all human languages stand in stark contrast to finite homesign communication systems that are lacking spatial prepositions, syntax, and other recursive elements of a formal sign language.

opencc-by-4.0Aug 2017View details →
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Figure 7 from: Underwood E, Grace M (2017) The use of biodiversity data in rural development programming. Research Ideas and Outcomes 3: e20369. https://doi.org/10.3897/rio.3.e20369

Figure 7 - Records added to the National Biodiversity Network Gateway, 2004 to 2015. From UK Biodiversity Indicators 2015, http://jncc.defra.gov.uk/page-4229 Source: NBN Gateway and NBN Atlas.

opencc-by-4.0Aug 2017View details →
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Figure 4 from: Vyshedskiy A, Mahapatra S, Dunn R (2017) Linguistically deprived children: meta-analysis of published research underlines the importance of early syntactic language use for normal brain development. Research Ideas and Outcomes 3: e20696. https://doi.org/10.3897/rio.3.e20696

Figure 4 - Synchronicity has to be understood in terms of synchronicity of the arrival of action potentials to a target neuron rather than absolute equality of action potential conduction times over different paths. Consider the following example: suppose neuron A is receiving excitatory input from neurons B and C via two different pathways (neuron A is the target neuron for both neurons B and C). Suppose that the action potential conduction time is 2ms from neuron B to neuron A and 22ms from neuron C to neuron A (i.e., the axonal pathway B-A has a significantly shorter conduction time than the axonal pathway C-A). Does it mean that the connections B-A and C-A are always asynchronous? No. The answer depends on the predominant neural activity rhythm in this network. At the firing rate of 50Hz (inter-spike interval of 20ms that correspond to Gamma rhythm), neurons B and C can actually be considered synchronous in relationship to neuron A: consider a train of action potentials synchronously fired by neurons B and C. The first action potential from neuron B will reach neuron A in 2ms and the first action potential from neuron C will reach neuron A in 22ms. Obviously, there would be no coincidence in the arrival times of the 1st action potentials from neurons B and C. However the second action potential from neuron B will arrive to neuron A in 22ms, concurrently with the 1st action potential from neuron C. Thus, starting with the second action potential, neuron A will receive synchronous activation from neurons B and C. The synchronous activation has a significantly greater probability of enhancing synaptic connections between neurons A and B, and A and C (Hebbian learning: 'neurons that fire together, wire together' (Hebb 1949). Thus, synchronicity does not need to imply absolute equality in the conduction time over different pathways. Rather synchronicity implies near-zero phase-shift between the two firing trains of action potentials at the postsynaptic cells. This phase-shift depends on conduction times over each pathway and also on the dominant firing frequency in the neural network.

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Figure 1 from: Underwood E, Grace M (2017) The use of biodiversity data in rural development programming. Research Ideas and Outcomes 3: e20369. https://doi.org/10.3897/rio.3.e20369

Figure 1 - Use of CMEF indicators in CAP monitoring and evaluation (reproduced from European Commission 2015)

opencc-by-4.0Aug 2017View details →
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Figure 2 from: Vyshedskiy A, Mahapatra S, Dunn R (2017) Linguistically deprived children: meta-analysis of published research underlines the importance of early syntactic language use for normal brain development. Research Ideas and Outcomes 3: e20696. https://doi.org/10.3897/rio.3.e20696

Figure 2 - A typical question testing subject's ability to mentally rotate an object is shown here as a 2x2 matrix with six answer choices displayed below the problem. The top row of the matrix indicates the rule: "the object in the right column is the result of 45° clockwise rotation." Applying this rule to the bottom row, we arrive at the correct answer depicted on the right.

opencc-by-4.0Aug 2017View details →
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Figure 6 from: Underwood E, Grace M (2017) The use of biodiversity data in rural development programming. Research Ideas and Outcomes 3: e20369. https://doi.org/10.3897/rio.3.e20369

Figure 6 - The German HNV monitoring methodology and results - HNV value decline In Germany, the HNV monitoring methodology has enabled an initial assessment of the trend in HNV value of farmland. Between 2009 and 2013, there was a significant decline of HNV value, in particular in the HNV class III, which represents the lowest value (in terms of species richness and structure). Graph reproduced from (Benzler et al. 2015).

opencc-by-4.0Aug 2017View details →
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Figure 3 from: Underwood E, Grace M (2017) The use of biodiversity data in rural development programming. Research Ideas and Outcomes 3: e20369. https://doi.org/10.3897/rio.3.e20369

Figure 3 - Extract of the Danish HNV map. Available at http://arealinformation.miljoeportal.dk/distribution/

opencc-by-4.0Aug 2017View details →
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Figure 1 from: Vyshedskiy A, Mahapatra S, Dunn R (2017) Linguistically deprived children: meta-analysis of published research underlines the importance of early syntactic language use for normal brain development. Research Ideas and Outcomes 3: e20696. https://doi.org/10.3897/rio.3.e20696

Figure 1 - Visual information processing in the cortex. From the primary visual cortex (V1, shown in yellow), the visual information is passed in two streams. The neurons along the ventral stream also known as the ventral visual cortex (shown in purple) are primarily concerned with what the object is. The ventral visual stream runs into the inferior temporal lobe. The neurons along the dorsal stream also known the dorsal visual cortex (shown in green) are primarily concerned with where the object is. The dorsal visual stream runs into the parietal lobe.

opencc-by-4.0Aug 2017View details →
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Figure 3 from: Vyshedskiy A, Mahapatra S, Dunn R (2017) Linguistically deprived children: meta-analysis of published research underlines the importance of early syntactic language use for normal brain development. Research Ideas and Outcomes 3: e20696. https://doi.org/10.3897/rio.3.e20696

Figure 3 - Linguistic isolates performance in verbal and nonverbal tests. This Figure is also available as a Power Point slide in Suppl. material 1.

opencc-by-4.0Aug 2017View details →
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Figure 5 from: Underwood E, Grace M (2017) The use of biodiversity data in rural development programming. Research Ideas and Outcomes 3: e20369. https://doi.org/10.3897/rio.3.e20369

Figure 5 - Opinions of RDP policy evaluators on data availability and bottlenecks. Results reproduced from ENRD 2012. A group of 58 RDP policy evaluators were asked about data availability and bottlenecks to data use for agricultural policy impact evaluation in 2007-2013. In response to the question: "To what extent are sound data available to carry out RDP impact evaluations?" 2% (1) replied 'fully available', 24% (14) replied 'largely available', 72% (42) replied 'partly available', 2% (1) replied 'not available'. The answers to the question "What are the major bottlenecks in providing sound data for the assessment of RDP impact in 2007-2013?" are shown in the graph.

opencc-by-4.0Aug 2017View details →
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Figure 2 from: Underwood E, Grace M (2017) The use of biodiversity data in rural development programming. Research Ideas and Outcomes 3: e20369. https://doi.org/10.3897/rio.3.e20369

Figure 2 - Workflow of the production of the EU Farmland Bird Index. Adapted from source: http://www.ebcc.info/wpimages/schema2016_big.jpg

opencc-by-4.0Aug 2017View details →
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Figure 1 from: Rane S, Jolly E, Park A, Jang H, Craddock C (2017) Developing predictive imaging biomarkers using whole-brain classifiers: Application to the ABIDE I dataset. Research Ideas and Outcomes 3: e12733. https://doi.org/10.3897/rio.3.e12733

Figure 1 - Weights (β-coefficients) for voxel-wise ReHo features from a support vector machine (SVM) classifier mapped on the glass brain to separate individuals with and without Autism Spectrum Disorder

opencc-by-4.0Mar 2017View details →

ScienceDex guides

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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.

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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.

allen-brain-atlas
neuroscienceopenDocumentation, web resources, and API references are available online.
Last verified 2026-04-30Open record

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.

abode-home-cage
behavioral-neuroscienceopenThe DataShare record exposes download links for annotations, documentation, license text, and the zipped per-snippet data directory.
Last verified 2026-04-30Open record

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.

dandi-nwb
electrophysiologyopenPublished Dandiset metadata and archive endpoints are available through the production DANDI API.
Last verified 2026-04-30Open record

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.

ibl
behavioral-neuroscienceopenPublic sessions can be searched and loaded from the IBL public data server through ONE.
Last verified 2026-04-29Open record

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.

openneuro
neuroscienceopenPublished datasets are available on demand over the internet.
Last verified 2026-04-29Open record