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Fig. 3 in Ecological fitting: Chemical profiles of plant hosts provide insights on selection cues and preferences for a major buprestid pest
Fig. 3. Average time spent (s ± 1SE) of gravid emerald ash borer females (Agrilus planipennis) in arms of Y-tube olfactometer with foliage emissions of olive (OL, Olea europaea), white fringetree (WF, Chionanthus virginica), green ash (GA, Fraxinus pennsylvanica), Manchurian ash (MA, F. mandshurica) or blank air (BL). (For interpretation of the references to colour in this figure legend, the reader is referred to the Web version of this article.)
Fig. 1 in Ecological fitting: Chemical profiles of plant hosts provide insights on selection cues and preferences for a major buprestid pest
Fig. 1. Mean emission rates of volatiles (ng/hour/g/foliage ± 1SE) of black ash (BA, Fraxinus nigra), blue ash (Blue, F. quadrangulata), Manchurian ash (MA, F. mandshurica), olive (OL, Olea europaea), and white fringetree (WF, Chionanthus virginicus), five plant hosts of emerald ash borer (Agrilus planipennis) collected in summer 2017. a) Overall plant profiles, b) antennally active compounds c) Green leaf volatile (GLV) profiles, d) sesquiterpene profiles, and e) Monoterpene profiles. (For interpretation of the references to colour in this figure legend, the reader is referred to the Web version of this article.)
Fig. 2 in Ecological fitting: Chemical profiles of plant hosts provide insights on selection cues and preferences for a major buprestid pest
Fig. 2. Ordination (nonmetric multidimensional scaling) plots of volatiles profiles of black ash (BA, Fraxinus nigra), blue ash (Blue, F. quadrangulata), Manchurian ash (MA, F. mandshurica), olive (OL, Olea europaea), and white fringetree (WF, Chionanthus virginicus), five plant hosts of emerald ash borer (Agrilus planipennis). a) Overall plant profiles, b) Green leaf volatile (GLV) profiles, c) monoterpene profiles, d) sesquiterpene profiles, and e) antennally active compounds. (For interpretation of the references to colour in this figure legend, the reader is referred to the Web version of this article.)
Fig. 5 in Transcriptome profiling of two Dactylis glomerata L. cultivars with different tolerance in response to submergence stress
Fig. 5. Gene Ontology (GO) classification of genes that only expressed differently in tolerant material 'Dianbei' and expressed differently between two materials all the time. (a) Gene Ontology (GO) classification of 1395 genes only expressed differently in tolerant material 'Dianbei'; (b) GO classification of 18 genes that were found to expressed differently between two materials all the time.
Fig. 1 in Transcriptome profiling of two Dactylis glomerata L. cultivars with different tolerance in response to submergence stress
Fig. 1. Hierarchical clustering analysis of changes in gene expression in two D. glomerata cultivars under submergence tolerance.
Fig. 3 in Transcriptome profiling of two Dactylis glomerata L. cultivars with different tolerance in response to submergence stress
Fig. 3. Gene Ontology (GO) classification of assembled unigenes in two D. glomerata cultivars, submergence-tolerant 'Dianbei' and submergence-sensitive 'Anba'.
Fig. 4 in Transcriptome profiling of two Dactylis glomerata L. cultivars with different tolerance in response to submergence stress
Fig. 4. Scatterplot of enriched KEGG pathways for differentially expressed genes between two D. glomerata cultivars.
Fig. 3 in The phenolic profile extracted from the desiccation-tolerant medicinal shrub Myrothamnus flabellifolia using Natural Deep Eutectic Solvents varies according to the solvation conditions
Fig. 3. Heatmap and dendrogram based on Euclidean distance and Ward's clustering algorithm. FSG = fructose–sucrose–glucose; Glu_ChCl = glucose–choline chloride; Pro_Mal = proline–malic acid; Su_Ca = sucrose–citric acid.
Figure 1 in The phenolic profile extracted from the desiccation-tolerant medicinal shrub Myrothamnus flabellifolia using Natural Deep Eutectic Solvents varies according to the solvation conditions
Figure 1. Principal component analysis scores plot indicating the sample groupings of the different NaDES extracts. This analysis was based only on the putative phenolic compounds. FSG = fructose–sucrose–glucose; Glu_ChCl = glucose– choline chloride; Pro_Mal = proline–malic acid; Su_Ca = sucrose–citric acid.
Fig. 4 in The phenolic profile extracted from the desiccation-tolerant medicinal shrub Myrothamnus flabellifolia using Natural Deep Eutectic Solvents varies according to the solvation conditions
Fig. 4. PCA biplot of the anthocyanins determined by HPLC. FSG = fructose–sucrose–glucose; Glu_ChCl = glucose–choline chloride; Pro_Mal = proline–malic acid; Su_Ca = sucrose–citric acid.
Fig. 5 in The phenolic profile extracted from the desiccation-tolerant medicinal shrub Myrothamnus flabellifolia using Natural Deep Eutectic Solvents varies according to the solvation conditions
Fig. 5. Bar plots showing the concentrations of the anthocyanins detected using HPLC in the different NaDES extracts. Values are based on the mean of three replicates. The error bars represent the standard deviation.
Supplementary material on serum metabolic profile for diagnosis of pathogen infection
<p>用于诊断病原体感染的血清代谢谱补充材料</p>
Color profiles of 108 UDGs identified in HFF fields
<p>Multi-band surface brightness profiles of 108 UDGs identified in HFF fields. Details about each diagram are listed below.<br> Panels\,(1) to (3) show the F814W band cutout-images of the UDG, the best-fitting GALFIT model and residual image. The bar at top-right of panel\,(2) represents 1.5\,kpc assuming the cluster redshift.<br> Panels\,(4) to (6) show PSF-matched images in F606W, F814W and F160W bands.<br> In panels\,(7) to (9), we mask neighboring sources classified by `Noisechisel' and overplot our elliptical annuli used in surface brightness analysis.<br> Panel\,(10) presents three-band surface brightness profiles of each UDG,<br> x-axis of colorful points correspond to the out-radius of elliptical annuli.<br> In panel\,(11), we convert observed color profiles into rest-frame U\,-\,V and V\,-\,I profiles.<br> F814W and F160W surface brightness profiles in panel\,(10) and rest-frame V\,-\,I profiles in panel\,(11) are shifted a bit to the right.<br> Finally, the colors of the UDG from inside to outside are shown in the UVI diagram in panel\,(12).<br> Please note that for UDGs which do not have F160W observations will not have panels (6),(9),(12).</p>
a Google Scholar search result and profiles dataset
<p>This dataset contains google scholar search result and profiles in jsonl format, and the original html pages of google scholar profiles. The search scope is mainly on computational chemistry and AI for science.</p>
High-resolution mass spectrometric profiling of stormwater in an Australian creek
<p>This data set contains high-resolution mass spectrometry raw (.wiff) data of urban stormwater samples collected from an Australian creek during a major storm event in 2020. The data were acquired in a SCIEX X500R QTOF instrument coupled to high-performance liquid chromatography (UHPLC) in ESI positive ionisation using both data dependant and data-independent (SWATH) modes. </p>
FIGURE 8 in Morphological and molecular profiling of an entomopathogenic nematode Steinernema feltiae: Unlocking its biocontrol potential against vegetable insect pests
FIGURE 8. Median lethal time (LT50) of Steinernema feltiae in the larvae of different insect pests at different time intervals and at different nematode concentrations, respectively.
FIGURE 6 in Morphological and molecular profiling of an entomopathogenic nematode Steinernema feltiae: Unlocking its biocontrol potential against vegetable insect pests
FIGURE 6. Maximum-likelihood phylogenetic tree between Steinernema feltiae and other species of Steinernema in the Feltiae-group based on nucleotide sequences of the D2–D3 expansion segments of large subunit (28S) of rRNA flanked by primers D2F and 536. Numbers at nodes represent bootstrap values based on 100 replications. Bars represent average nucleotide substitutions per sequence position. NCBI accession numbers of the nucleotide sequences used for the analyses are shown next to the species names. The scale bar shows the number of substitutions per site.
FIGURE 4 in Morphological and molecular profiling of an entomopathogenic nematode Steinernema feltiae: Unlocking its biocontrol potential against vegetable insect pests
FIGURE 4. Steinernema feltiae (light microscopy). A–C: First-generation female; A: Neck region (arrow pointing excretory pore); B: Vulva region; C: Posterior end (arrow pointing mucron). D,E: First-generation male; D: Neck region (arrow pointing excretory pore); E: Posterior end showing spicules and gubernaculum (arrow pointing mucron). F,G: Second-generation male; F: Neck region (arrow pointing excretory pore); G: Posterior end showing spicules and gubernaculum (arrow pointing mucron). H–J: Second-generation female; H: Neck region (arrow pointing excretory pore); I: Vulva region; J: Posterior end (arrow pointing mucron).
FIGURE 2 in Morphological and molecular profiling of an entomopathogenic nematode Steinernema feltiae: Unlocking its biocontrol potential against vegetable insect pests
FIGURE 2. Steinernema feltiae (line). A–D: First-generation female; A: Neck region; B: Posterior end; C: Vulva region; D: Whole female. E,G–K: Second-generation female; E: Whole female; G: Neck region; H–J: Posterior region showing variation in tail region; K: Vulva region. F: Whole infective juvenile.
FIGURE 3 in Morphological and molecular profiling of an entomopathogenic nematode Steinernema feltiae: Unlocking its biocontrol potential against vegetable insect pests
FIGURE 3. Steinernema feltiae (line). A–C: First-generation male; A: Whole male; B–C: Posterior region showing variations in spicule morphology. D,E: Second-generation male; D: Whole male; E: Posterior region.
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.