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ShareScore release 0.9.0
Dataset results
6 results for “in situ visualization”
MiL-FISH: Multi-labelled oligonucleotides for fluorescence in situ hybridisation improve visualization of bacterial cells
<p>Comparison of mono-, MiL- and CARD-FISH on LR-White embedded <em>Olavius algarvensis</em> cross sections A: Ethanol preserved specimen, cu = cuticle, sym = symbionts, sep = septum, epi = epidermis, mu = muscle, vbv = ventral blood vessel & nerve chord, chl = chloragogen tissue, grid square = example of region shown in images B, C, D and E.</p> <p>Probes for Gammaproteobacteria (Gam42a; green) and a subgroup of sulfate-reducing Deltaproteobacteria (DSS658; red) on B) mono-FISH on ethanol preserved specimen, 19 hour hybridisation. C) mono-FISH on ethanol preserved specimen, 3 hour hybridisation and D) CARD-FISH on Carnoy’s / PFA fixed specimen, 3-hour hybridisation. E) MiL-FISH on Carnoy’s / PFA fixed specimen, 3 hour hybridisation. Scale bar = 5 µm.</p>
MiL-FISH: Multi-labelled oligonucleotides for fluorescence in situ hybridisation improve visualization of bacterial cells
<p>Sections of LR-White embedded <em>Olavius algarvensis </em>eggs. A) DAPI stained overview of egg after first cleavage, grid square = region in B, cle = cleavage. B) Gamma- (ii) and Delta- (i) proteobacteria hybridised with 4x labelled Gam42a & 4x labelled DSS658 probe respectively. Autofluorescence of egg yolk is overcome and bacteria are seen to closely associated with the developing embryo. y = egg yolk C) DAPI stained overview of juvenile worm in egg, grid square = region in D. D) Gamma 1 symbiont phylotype (iii) hybridised with 16S rRNA specific probe labelled with 2x FITC and 2x Cy3 to produce yellow in the overlay. Symbiont cells are incorporated between cuticle and epidermis and in close proximity to egg yolk. y = egg yolk, c = cuticle. Scale: A & C = 50 µm, B & D = 5 µm.</p>
MiL-FISH: Multi-labelled oligonucleotides for fluorescence in situ hybridisation improve visualization of bacterial cells
<p>Epifluorescence images of MiL-FISH labelled microorganisms: A) <em>Beggiatoa sp. </em>hybridised with Gam42a, B) <em>Desulfococcus biacutus </em>with DSS658, C) <em>Roseobacter sp. </em>with Ros537, D) <em>Sulfurimonas denitrificans </em>with EPSY914, E) <em>Rhodopirellula sp. </em>SH1 T with PLA46, F) <em>Gramella forsetii </em>with CF319a, G) <em>Metallosphaera sedula </em>with Arch915, H) Composite image of all seven microbial partners in an artificial mix. Letters correlate to images of individual organisms A-G. Scale bar: A & H = 10 µm, B-G = 5 µm.</p> <p>From:</p> <p>Schimak MP, Kleiner M, Wetzel S, Liebeke M, Dubilier N, Fuchs BM. 2015. MiL-FISH: Multi-labelled oligonucleotides for fluorescence in situ hybridisation improve visualization of bacterial cells. Applied and Environmental Microbiology. Accepted manuscript posted online. doi:10.1128/AEM.02776-15</p>
Audio Visual in-situ Monitoring Dataset for Laser Directed Energy Deposition (LDED) of Maraging Steel C300
<p>This dataset presents a set of acoustic signals and coaxial CCD images captured during a single-bead wall experiment in robotic Laser Directed Energy Deposition (LDED) using Maraging Steel C300. The acoustic data was recorded using a high-fidelity Prepolarized microphone sensor (Xiris WeldMIC), capturing the intricate sound profiles associated with the LDED process at a sampling rate of 44,100 Hz. The coaxial CCD melt pool images are captured at 30 Hz.</p> <p><strong>Laser Directed Energy Deposition:</strong></p> <p>This dataset was generated with a robotic LDED process that consists of a six-axis industrial robot (KUKA KR90) coupled with a two-axis positioner, a laser head, and a coaxial powder-feeding nozzle.</p> <p> </p> <p><strong>File Naming Convention:</strong></p> <ul> <li>Audio files within the <strong>audio_files</strong> folder are named following the pattern <strong>sample_ExperimentID_SampleID.wav</strong>. Given that there's only one experiment and one sample provided in this demo dataset, the naming will be consistent, for example, <strong>sample_1_1.wav</strong> for the first file.</li> <li>Coaxial melt pool image files within the <strong>images </strong>folder are named following the pattern <strong>sample_ExperimentID_SampleID.jpg</strong>. </li> </ul> <p><strong>Annotation Details:</strong></p> <ul> <li>The <strong>annotations_1.csv</strong> file contains detailed labels for each audio file and image file, correlating to the conditions observed during the experiment, aiding in quick identification and analysis.</li> </ul> <p><strong>Handcrafted features for ML modelling:</strong></p> <ul> <li>The <strong>audio_features.h5</strong> file contains various physics-informed acousitc feature extracted through Python, which can be used for baseline ML modelling purpose.</li> </ul> <p><strong>Experimental Parameters:</strong> The dataset reflects a controlled experiment setup with the following specifications:</p> <ul> <li>Geometry: Single bead wall structure</li> <li>Dimensions: 90 mm * 42.5 mm</li> <li>Number of layers: 50</li> <li>Laser beam diameter: 2 mm</li> <li>Layer thickness: 0.85 mm</li> <li>Stand-off distance: 12 mm</li> <li>Laser profile: Gaussian</li> <li>Laser wavelength: 1064 nm</li> </ul> <p><strong>Process Parameters:</strong></p> <ul> <li>Laser power: 2.3 kW</li> <li>Speed: 25 mm/s</li> <li>Dwell time: 0 s</li> <li>Powder flow rate: 12 g/min</li> </ul> <p>This dataset aims to facilitate the development and testing of acoustic-based, or multi-sensor fusion-based defect detection models for real-time quality monitoring in LDED processes. It can also serve as a reference point for further research on sensor fusion, machine learning, and real-time monitoring of manufacturing processes.</p>
The local cellular response to Human Papillomavirus focuses on basal layer restoration as visualized in situ by specific cellular neighborhoods near infected cells
GEO Series GSE311892. Homo sapiens. 36 samples. Type: Other.
A verified open-access AI-based chemical microparticle image database for in-situ particle visualization and quantification in multi-phase flow
<p>This report provided a new method and idea for the detection, segmentation, classification, and quantitative analysis of four dispersed phase particles - "DPPs" (agglomeration, bubble, crystal, and droplet) in chemical multi-phase flow processes.</p>
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.