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1,630 results for “Stepping”
Characteristic and Mechanism of Step-rising Pressure-Stimulated Rock Current from Dried Diorite Bi-axially Compressed to Failure
<p>The data of AE and PSRC of seven partly bi-axially dried diorite samples (FDB1-FDB7). The AE signals collection of specimen FDB1 was invalidated. For example, The file named 'FDB2-AE and PSRC.xlsx' contains the AE data in Sheet1 and PSRC in Sheet2. The file named 'FDB2-stress.xlsx' contains stress and dislpacement of main and side axial. Other documents are the same as FDB2. The file named 'AE.m' is the Matlab code to calcuate shear micro-cracks ratio and plot relevant figures.</p>
Dataset for the publication Demonstration of dual Shapiro steps in small Josephson junctions
<p>This dataset set provides all the measurement data in txt file nedded to generate the figures in the article. Furthermore the three databases with all taken data of the sample is provided</p>
FIGURE 3 in Second-step lectotypification of the name Taxus chienii (Taxaceae)
FIGURE 3. One syntype (S. Chen 1384, PE) of Taxus chienii, which was selected as the lectotype by Lin & Cao (2007) and might be superseded. Permission by Herbarium of Institute of Botany, Chinese Academy of Sciences (PE).
FIGURE 1 in Second-step lectotypification of the name Taxus chienii (Taxaceae)
FIGURE 1. Law's indication of type for Taxus chienii in Botanical Bulletin of Academia Sinica 1: 144. 1947. Underlined by the author.
FIGURE 4 in Second-step lectotypification of the name Taxus chienii (Taxaceae)
FIGURE 4. One syntype (S. Chen 3024, PE) of Taxus chienii. Permission by Herbarium of Institute of Botany, Chinese Academy of Sciences (PE).
FIGURE 2 in Second-step lectotypification of three names of Araceae from India
FIGURE 2. Lectotype of Arisaema nepenthoides (Wall.) Mart. ex Schott [Wallich Cat. No. 8919, (K001131838) A & B, designated here] © Royal Botanic Gardens, Kew (Available online from http://apps.kew.org/herbcat/getImage.do?imageBarcode=K001131838).
FIGURE 1 in Second-step lectotypification of three names of Araceae from India
FIGURE 1. Lectotype of Arisaema echinatum (Wall.) Schott [Wallich Cat. No. 8916 (K001131834) A–C, designated here] © Royal Botanic Gardens, Kew (Available online from http://apps.kew.org/herbcat/getImage.do?imageBarcode=K001131834).
FIGURE 1. Campuloclinium alternifolium Gardner. A in Following the Gardner steps: re-collection of Campuloclinium alternifolium (Compositae) after 177 years
FIGURE 1. Campuloclinium alternifolium Gardner. A. Habitat (white arrow indicates the forest where this species was found). B. Habit herbaceous, erect. C. Synflorescence with alternate synflorescence bracts similar to upper cauline leaves. Photographs by J. Calvo.
FIGURE 2. Campuloclinium alternifolium Gardner. A. Capitulum. B. Membranaceous cauline leaf. C in Following the Gardner steps: re-collection of Campuloclinium alternifolium (Compositae) after 177 years
FIGURE 2. Campuloclinium alternifolium Gardner. A. Capitulum. B. Membranaceous cauline leaf. C. Opposite arrangement of the cauline leaves (white arrows indicate the leaf petioles). D. Roots. Photographs by J. Calvo.
Raw NMR FID Data for Iodide Enhanced the Production of Pseurotin D over Pseurotin A by Inverting the Preference of SN2 versus SN2′ Competition in the Last Non-Enzymatic Biosynthetic Step
<p>This is a NMR FID data for manuscript titled "Iodide Enhanced the Production of Pseurotin D over Pseurotin A by Inverting the Preference of SN2 versus SN2′ Competition in the Last Non-Enzymatic Biosynthetic Step", which is currently under review.</p>
FIGURE 1 in Second-step lectotypification of the name Wormia mansonii, the basionym of Dillenia mansonii (Dilleniaceae)
FIGURE 1. Second step lectotype of Wormia mansonii, the basionym of Dillenia mansonii. CAL0000004061 (digital image!) © Botanical Survey of India, CAL.
One-Step Photochemical Immobilization of Aptamer on Graphene for Label-Free Detection of NT-proBNP
<p>A novel photochemical technological route for one-step functionalization of a graphene surface with an azide-modified DNA aptamer for biomarkers is developed. The methodology is demonstrated for the functionalization of a DNA aptamer for an N-terminal B-type natriuretic peptide (NT-proBNP) heart failure biomarker on the surface of a graphene channel within a system based on a liquid-gated graphene field effect transistor (GFET). The limit of detection (LOD) of the aptamer-functionalized sensor is 0.01 pg/mL with short response time (75 s) for clinically relevant concentrations of the cardiac biomarker, which could be of relevance for point-of-care (POC) applications. The novel methodology could be applicable for the development of different graphene-based biosensors for fast, stable, real-time, and highly sensitive detection of disease markers.</p>
Data from: Improving genomic prediction for two Yorkshire populations with a limited size using single-step method
In this study, we conducted genomic prediction for two Yorkshire purebred populations (Yichun and Chifeng) from two different provinces of China that both had a limited population size. Two growth traits (age adjusted to 100 kg weight, AGE; back‐fat thickness adjusted to 100 kg weight, BF) and one reproduction trait (total number of piglets born, TNB) were analyzed with four prediction strategies: one‐population BLUP, joint two‐population BLUP, one‐population single‐step BLUP (SSBLUP) and joint two‐population SSBLUP. Our results illustrate that accuracies of genomic estimated breeding values were improved for BF and TNB for the Yichun population and for BF for the Chifeng population by genomic prediction (one‐population SSBLUP and joint two‐population SSBLUP). The accuracy of TNB for the Yichun population was increased two fold when comparing the one‐population SSBLUP to the one‐population BLUP prediction. Meanwhile, prediction biases were dramatically reduced for AGE for the Yichun population and for TNB for the Chifeng population. The conclusions of this study are as follows: first, genomic prediction is useful for improving prediction accuracy for purebred pig breeding farms with a limited population size; second, joint genomic prediction for different populations of the same breed with certain genetic links has the trend to further improve prediction accuracy.
Data from: Characterizing wildlife behavioural responses to roads using integrated step selection analysis
Roads are a prevalent, ever-increasing form of human disturbance on the landscape. In many places in western North America, energy development has brought human and road disturbance into seasonal winter range areas for migratory elk. We sought to evaluate the predictions from the risk-disturbance hypothesis when studying elk response to roads during winter. Road proximity and crossing were used to evaluate these behaviours, which offered a rare comparison between two common measures of roads. We used integrated step selection analysis (iSSA) to evaluate four alternative hypotheses regarding the influence of roads on space-use behaviour across 175 elk-years of elk telemetry data, and we quantified both population-level and individual-level variations in responses. We demonstrated, for the first time, how iSSA can be used to combine movement analysis in a refined approach to habitat selection. Elk responded to roads as they would natural predation risk. Elk selected areas farther from roads at all times of day with avoidance being greatest during twilight. In addition, elk sought cover and moved more when in the vicinity of roads. Road crossings were generally avoided, but this avoidance was weakest during daytime when elk were both moving and closer to roads. Synthesis and applications. Energy development is transforming landscapes in western North America with the proliferation of roads, which we show is having substantial and multifaceted negative effects on elk movement and behaviour. These adverse effects can be mitigated by minimizing new road construction and by restricting traffic on roads as well as providing the protection of tree cover on elk winter ranges.
Figure 2 in Superimposition of the sting morphological characters on the dendrogram of Apoidea with emphasis on Crabronidae s. str. (Insecta: Hymenoptera): first steps
Figure 2. Sting parts of Lestica alata. (a) – lateral parts of tergite 9, dorsal view; (b) – lateral sclerite of tergite 9, medial view; (c) – furcula, lateral view; (d) – 2nd valvula, lateral view; (e) – the 2nd ramus, fused with the rostral process of the 2nd valvifer, laterofrontal view; (f) – the 3rd valvula, lateral view; (g) – apical cone-shaped process of the 3rd valvula, laterodorsal view; (h) – the 1st valvula+1st ramus +1st valvifer, medial view; I–valvillus, medial view; (j) – the 1st and 2nd valvulae, lateral view. A, C, D – LM; B, E-J – SEM. Arrowheads indicate regions of interest. Scale bars: 200 µm in A and D; 100 µm – in B, F, H; 50 µm – in C; 20 µm – in E, G, I, J. l – lateral direction; p – posterior direction; v–ventral direction.
Figure 1 in Superimposition of the sting morphological characters on the dendrogram of Apoidea with emphasis on Crabronidae s. str. (Insecta: Hymenoptera): first steps
Figure 1. Sting parts of Bembicinus hungaricus. (a) – the lateral parts of tergite 9, dorsal view, LM; (b) – lateral part of tergite 9, medial view; (c) – furcula, lateral view; (d) – the 2nd valvula, ventrolateral view; (e) – the 2nd ramus, fused with the rostral process of the 2nd valvifer, laterofrontal view; (f) – the 3rd valvula, lateral view; (g) – apical cone-shaped process of the 3rd valvula, ventral view; (h) – the 1st valvula + the 1st ramus + the 1st valvifer, medial view, scale bar; I–valvillus, medial view; J – the 1st valvula, lateral view. B-J – SEM. Arrowheads indicate regions of interest. Scale bars: 200 µm in A and D; 100 µm – in B, F, H; 50 µm – in C; 20 µm – in E, G, I, J. l – lateral direction; p – posterior direction; v– ventral direction.
Figure 5 in Superimposition of the sting morphological characters on the dendrogram of Apoidea with emphasis on Crabronidae s. str. (Insecta: Hymenoptera): first steps
Figure 5. The character states, symbolically superimposed on the simplified dendrogram, resultant from a combination of molecular phylogenies provided by previous students. (Peters et al. 2017; Sann et al. 2018). The dark shading indicates tentative synapomorphies.
Figure 4 in Superimposition of the sting morphological characters on the dendrogram of Apoidea with emphasis on Crabronidae s. str. (Insecta: Hymenoptera): first steps
Figure 4. Sting parts of Sceliphron curvatum. (a) – lateral parts of tergite 9, dorsal view; (b) – lateral sclerite of tergite 9, medial view; (c) – furcula, lateral view; (d) – 2nd valvula, lateral view; (e) – the 2nd ramus, fused with the rostral process of the 2nd valvifer, laterofrontal view; (f) – the 3rd valvula, lateral view; (g) – apical cone-shaped process of the 3rd valvula, ventral view; (h) – the 1st valvula+1st ramus +1st valvifer, lateral view; (i)–valvillus, lateral view; (j) – the 1st and 2nd valvulae, lateroventral view. A, C, D – LM; B, E-J – SEM. Arrowheads indicate regions of interest. Scale bars: 200 µm in A and D; 100 µm – in B, F, H; 50 µm – in C; 20 µm – in E, G, I, J. l – lateral direction; p – posterior direction; v– ventral direction.
Figure 3 in Superimposition of the sting morphological characters on the dendrogram of Apoidea with emphasis on Crabronidae s. str. (Insecta: Hymenoptera): first steps
Figure 3. Sting parts of Crabro scutellatus. (a) – lateral parts of tergite 9, dorsal view; (b) – lateral sclerite of tergite 9, medial view; (c) – furcula, lateral view; (d) – 2nd valvula, lateral view, scale bar; (e) – the 2nd ramus, fused with the rostral process of the 2nd valvifer, laterofrontal view; (f) – the 3rd valvula, lateral view; (g) – apical cone-shaped process of the 3rd valvula, laterodorsal view; (h) – the 1st valvula +1st ramus+1st valvifer+2ndramus+2nd valvifer; (i)–valvillus, medial view; (j) – the 1st and 2nd valvulae, lateral view. A-D – LM; E-J – SEM. Arrowheads indicate regions of interest. Scale bars: 200 µm in A and D; 100 µm – in B, F, H; 50 µm – in C; 20 µm – in E, G, I, J. l – lateral direction; p – posterior direction; v– ventral direction.
Data from: Scrutinizing key steps for reliable metabarcoding of environmental samples
1. Metabarcoding of environmental samples has many challenges and limitations that require carefully considered laboratory and analysis pipelines to ensure reliable results. We explore how decisions regarding study design, laboratory work and bioinformatic processing affect the final results, and provide guidelines for reliable study of environmental samples. 2. We evaluate the performance of four primer sets targeting COI and 16S regions characterising arthropod diversity in bat faecal samples, and investigate how metabarcoding results are affected by parameters including: i) number of PCR replicates per sample, ii) sequencing depth, iii) PCR replicate processing strategy (i.e. either additively, by combining the sequences obtained from the PCR replicates, or restrictively, by only retaining sequences that occur in multiple PCR replicates for each sample), iv) minimum copy number for sequences to be retained, v) chimera removal, and vi) similarity thresholds for OTU clustering. Lastly, we measure within- and between-taxa dissimilarities when using sequences from public databases to determine the most appropriate thresholds for OTU clustering and taxonomy assignment. 3. Our results show that the use of multiple primer sets reduces taxonomic biases and increases taxonomic coverage. Taxonomic profiles resulting from each primer set are principally affected by how many PCR replicates are carried out per sample and how sequences are filtered across them, the sequence copy number threshold and the OTU clustering threshold. We also report considerable diversity differences between PCR replicates from each sample. Sequencing depth increases the dissimilarity between PCR replicates unless the bioinformatic strategies to remove allegedly artefactual sequences are adjusted according to the number of analysed sequences. Finally, we show that the appropriate identity thresholds for OTU clustering and taxonomy assignment differ between target markers. 4. Metabarcoding of complex environmental samples ideally requires i) investigation of whether more than one primer sets targeting the same taxonomic group is needed to offset the effect of primer biases, ii) more than one PCR replicate per sample, iii) bioinformatic processing approaches of sequences that balance diversity detection with removal of artificial sequences, and iv) empirical selection of OTU clustering and taxonomy assignment thresholds tailored to each genetic marker and the obtained taxa.
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Allen Brain Atlas
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International Brain Laboratory public data
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OpenNeuro
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