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12,393 results for “materiality”
FIGURE 13 in The type material of spider wasps (Hymenoptera, Pompilidae) deposited in the Federal Scientific Center of the East Asia Terrestrial Biodiversity, Russian Academy of Sciences, Vladivostok, Russia
FIGURE 13. Arachnospila orientausa Loktionov & Lelej, 2011, ♂, holotype. A. Labels. B. Habitus, lateral view. C. Head, dorsal view. D. Head, lateral view. E. Head, frontal view. F. Hypopygium and sternum 7, ventral view. G. Hypopygium, lateral view. H. Genitalia, ventral view. Scale bar: 1.0 mm for B; 0.5 mm for F, G, H; 0.2 mm for C, D, E. F, H, G from Loktionov & Lelej 2011.
FIGURE 25 in The type material of spider wasps (Hymenoptera, Pompilidae) deposited in the Federal Scientific Center of the East Asia Terrestrial Biodiversity, Russian Academy of Sciences, Vladivostok, Russia
FIGURE 25. Kuriloagenia ermolenkoi Loktionov & Lelej, 2014, ♂, holotype. A. Labels. B. Habitus, lateral view. C. Head, lateral view. D. Head, dorsal view. E. Head, frontal view. F. Hypopygium and sternum 7, ventral view. G. Genitalia, ventral view. Scale bar: 1.0 mm for B; 0.5 mm for F, G; 0.2 mm for C, D, E. F, G from Loktionov & Lelej 2014.
Supplementary materials to "Brakenhoff et al., Application of time series analysis to estimate drawdown from multiple well fields."
<p>This repository contains the supplementary material that allow to reproduce all the results from the study submitted to Frontiers journal.</p> <p> </p>
Supplementary Materials of remotesensing-1447006
<p>Supplementary Material 1: Specification files (.rda format) for each model fitted in the present study.<br> Supplementary Material 2: Predictor’s loading values and contribution for the explained variability for each dimension of the optimized PLSR models.</p>
Supplemental material for: Validation of intraluminal filling defect length to identify carotid free-floating thrombus in patients with stroke/TIA
<p><strong>Objective: </strong>To validate a previously proposed filling defect length threshold of >3.8 mm on CT-angiography (CTA) to discriminate between free-floating thrombus (FFT) and plaque of atheroma.</p> <p><b>Materials and Methods: </b>Prospective multicenter observational study of 100 participants presenting with TIA/stroke symptoms and a carotid intraluminal filling defect on initial CTA. Follow-up CTA was obtained within one week, and at weeks 2 and 4 if the intraluminal filling defect was unchanged in length. Resolution or decreased length was diagnostic of FFT, whereas its static appearance after 4 weeks was indicative of plaque. Diagnostic accuracy of FFT length was assessed by receiver operating characteristic analysis.</p> <p><b>Results: </b>Ninety-five participants (mean age [standard deviation], 68 [13] years; 61 men; 83 participants with FFT; 12 participants with a plaque) were evaluated. The >3.8 mm threshold had a sensitivity of 88% (73/83) (95% confidence interval {CI}: 78%, 94%) and specificity of 83% (10/12) (95% CI, 51%, 97%) (area under the curve [AUC], 0.91, p<.001) for the diagnosis of FFT. The optimal length threshold was >3.64 mm with a sensitivity of 89%( 74/83) (95% CI, 80%, 95%) and specificity of 83% (10/12) (95% CI, 51%, 97%). Adjusted logistic regression showed that every 1 mm increase in intraluminal filling defect length is associated with an increase in odds of FFT of 4.6 ([95% CI] 1.9-11.1; <i>p</i>=.01).</p> <p><b>Conclusion: </b>CTA enables accurate differentiation of FFT versus plaque using craniocaudal length thresholds.</p> <p><strong>Clinical Trial Identifier:</strong> <a href="http://www.clinicaltrials.gov">www.clinicaltrials.gov</a> NCT02405845.</p> <p><b>Classification of Evidence: </b>This study provides Class I evidence that in patients with TIA/stroke symptoms, the presence of a carotid intraluminal filling defect with length > 3.8 mm on CTA accurately discriminates free-floating thrombus from atheromatous plaque.</p>
Supplementary material of "VIGIL: A Python tool for automatized probabilistic VolcanIc Gas dIspersion modeLling"
<p>This dataset includes the Supplementary material of the paper: </p> <p>Dioguardi F, Massaro S, Chiodini G, Costa A, Folch A, Macedonio G, Sandri L, Selva J, Tamburello G. VIGIL: A Python tool for automatized probabilistic VolcanIc Gas dIspersion modeLling. Ann. Geophys. [Internet]. 2022Apr.3 [cited 2022Apr.7];65(1). Available from: https://www.annalsofgeophysics.eu/index.php/annals/article/view/8796</p>
Supplementary material 1 from: Chua PYS, Carøe C, Crampton-Platt A, Reyes-Avila CS, Jones G, Streicker DG, Bohmann K (2022) A two-step metagenomics approach for the identification and mitochondrial DNA contig assembly of vertebrate prey from the blood meals of common vampire bats (Desmodus rotundus). Metabarcoding and Metagenomics 6: e78756. https://doi.org/10.3897/mbmg.6.78756
A two-step metagenomics approach for prey identification from the blood meals of common vampire bats (Desmodus rotundus)
Potential and limits of cultivation of brackish and freshwater populations of tubular morphotypes of Ulva (Ulvophyceae) in food industry or biotechnologies -supplementary material
<p>Supplementary material for diploma thesis: Potential and limits of cultivation of brackish and freshwater populations of tubular morphotypes of Ulva (Ulvophyceae) in food industry or biotechnologies.</p>
Supplementary Materials for Potential Health and Economic Impacts of Shifting Manufacturing from China to Indonesia or India
<p>The Supplementary Materials for ariticle <em>Potential Health and Economic Impacts of Shifting Manufacturing from China to Indonesia or India. </em></p>
Supplementary material 1 from: Murphy CA, Gerth W, Neal T, Arismendi I (2022) A low-cost, durable, submersible light trap and customisable LED design for pelagic deployment and capture of fish parasite Salmincola sp. copepodids. NeoBiota 73: 1-17. https://doi.org/10.3897/neobiota.73.76515
Supplementary material for a low-cost, durable, submersible light trap and customizable LED design for pelagic deployment and capture of fish parasite Salmincola sp. copepodids
Supplementary material for "A collection of Constraint Programming models for the three-dimensional stable matching problem with cyclic preferences"
<p>No external dependency is needed to compile the code, but MiniZinc is required to run it. Running the code without any argument will give the instructions.</p>
Material complementario - Las técnicas constructivas de las fortificaciones medievales
<p>Material complementario del capítulo</p> <p>Las técnicas constructivas de las fortificaciones medievales de la Alpujarra granadina (siglos VI-XV) presentado en el <em>XII Congreso nacional de la Sociedad Española de Historia de la Construcción</em></p>
Supplement material from: Plasma levels of triglycerides and IL6 are associated with weight regain and fat mass expansion
<p><strong>Background/Objective:</strong> Long-term weight loss (WL) maintenance is the biggest challenge for overweight and obesity due to the almost unavoidable phenomenon of partial or even total weight regain (WR) after WL. In the current study we investigated the relations of (the changes of) adipocyte size and other risk biomarkers with WR during the follow up of the Yoyo dietary intervention.</p> <p><strong>Design:</strong> In this randomized controlled study, 48 overweight/obese participants underwent a (very) low calorie diet to lose weight, followed by a weight stable period of 4 weeks and a follow-up period of 9 months. Anthropometric measurements, adipocyte volume of abdominal subcutaneous adipose tissue and plasma metabolic parameters (FFA, TG, total cholesterol, glucose, insulin, HOMA-IR, IL6, ACE activity, RBP4) at the beginning and the end of the follow-up were analyzed.</p> <p><strong>Results:</strong> Our results show that changes of TG, IL6, HOMA-IR and ACE are significantly positively correlated with WR. Multiple linear regression analysis shows that only the changes of TG and IL6 remained significantly correlated with WR and increased body fat mass. Moreover, the change of HOMA-IR was tightly correlated with the change in TG. Surprisingly, the change of adipocyte volume during follow up was not correlated with WR nor with other factors, but positive correlations between adipocyte volume and HOMA-IR were found at the beginning and end of the follow up.</p> <p><strong>Conclusions: </strong>These results suggest that TG and IL6 are independently linked to WR via separate mechanisms, and that HOMA-IR and adipocyte volume may indirectly link to WR through the change of plasma TG.</p>
Radar Station Supplementary Material 1/2
<p># Radar Station data file. <br> <br> This repo contains the data necessary for the paper 'Radar Station: Using KG Embeddings for Semantic Table Interpretation and Entity Disambiguation.'<br> <br> The second part of the data is available at https://zenodo.org/record/6522921<br> <br> Its structure of it is as follows:<br> <br> '''<br> ├─readme.md<br> ├─DAGOBAHSL_Scoring<br> │ ├─Limaye_Result<br> │ ├─T2D_Result<br> │ ├─2T_Result<br> │ ├─ShortTable_Result<br> ├─Embeddings<br> │ ├─RotetE<br> │ ├─ComplEx<br> │ ├─TransE<br> │ ├─Dismult<br> ├─Datasets<br> │ ├─Key_Column_Index<br> │ │ ├─Limaye<br> │ │ ├─T2D<br> │ ├─ShortTable<br> ├─Wikidata_Ground_Truth<br> │ ├─Wikidata_GS_Limaye<br> │ ├─Wikidata_GS_T2D<br> │ ├─Wikidata_GS_2T<br> │ ├─Wikidata_GS_ShortTable<br> '''<br> <br> ## DAGOBAHSL_Scoring<br> It contains the result of the candidate scoring step after the four datasets were processed through a previous annotation system.<br> In this score step, we did not filter any candidates during the calculation and always kept their scores. <br> <br> <br> ## Embeddings<br> <br> This folder contains four embeddings used during our experiment.<br> We provide four embeddings for the experiments: TransE, RotatE, Dismult, and ComplEx. <br> In which the RotatE embeddings are from the pre-trained embeddings of GraphVite: https://graphvite.io/docs/latest/pretrained_model.html <br> TransE, Dismult, and ComplEx are trained using Pytorch-BigGraph with Wikidata dump version 2021 May.<br> <br> **NOTICE**: the Dismult and ComplEx Embeddings should be further added to this folder.<br> <br> <br> ## Datasets<br> ### Key_Column_Index<br> <br> Key_Column_Index folder contains the index of the key column position for T2D and Limaye that are manually annotated.<br> It tells Radar Station in which column we should run.<br> <br> ### ShortTable<br> <br> It contains the ShortTable dataset with tables of only two rows.<br> <br> ## Wikidata_Ground_Truth<br> It contains the ground truth of the four datasets with Wikidata entities.</p>
Radar Station Supplementary Material 2/2
<p># Radar Station data file. <br> <br> This repo contains the data necessary for the paper 'Radar Station: Using KG Embeddings for Semantic Table Interpretation and Entity Disambiguation.'<br> <br> The first part of the data is available at https://zenodo.org/record/6522985<br> <br> Its structure of it is as follows:<br> <br> '''<br> ├─readme.md<br> ├─DAGOBAHSL_Scoring<br> │ ├─Limaye_Result<br> │ ├─T2D_Result<br> │ ├─2T_Result<br> │ ├─ShortTable_Result<br> ├─Embeddings<br> │ ├─RotetE<br> │ ├─ComplEx<br> │ ├─TransE<br> │ ├─Dismult<br> ├─Datasets<br> │ ├─Key_Column_Index<br> │ │ ├─Limaye<br> │ │ ├─T2D<br> │ ├─ShortTable<br> ├─Wikidata_Ground_Truth<br> │ ├─Wikidata_GS_Limaye<br> │ ├─Wikidata_GS_T2D<br> │ ├─Wikidata_GS_2T<br> │ ├─Wikidata_GS_ShortTable<br> '''<br> <br> ## DAGOBAHSL_Scoring<br> It contains the result of the candidate scoring step after the four datasets were processed through a previous annotation system.<br> In this score step, we did not filter any candidates during the calculation and always kept their scores. <br> <br> <br> ## Embeddings<br> <br> This folder contains four embeddings used during our experiment.<br> We provide four embeddings for the experiments: TransE, RotatE, Dismult, and ComplEx. <br> In which the RotatE embeddings are from the pre-trained embeddings of GraphVite: https://graphvite.io/docs/latest/pretrained_model.html <br> TransE, Dismult, and ComplEx are trained using Pytorch-BigGraph with Wikidata dump version 2021 May.<br> <br> **NOTICE**: The folder <em>ComplEx </em>and <em>DistMult </em>should be placed in the folder <em>Embeddings </em>for enabling Radar Station<br> <br> <br> ## Datasets<br> ### Key_Column_Index<br> <br> Key_Column_Index folder contains the index of the key column position for T2D and Limaye that are manually annotated.<br> It tells Radar Station in which column we should run.<br> <br> ### ShortTable<br> <br> It contains the ShortTable dataset with tables of only two rows.<br> <br> ## Wikidata_Ground_Truth<br> It contains the ground truth of the four datasets with Wikidata entities.</p> <p> </p>
Figure 15 in Reappraisal and new material of the holotype of Draconyx loureiroi (Ornithischia: Iguanodontia) provide insights on the tempo and modo of evolution of thumb-spiked dinosaurs
Figure 15. Life restoration of Draconyx loureiroi, in the environment represented by Lourinhã Formation. Credit: Victor Carvalho, used with permission under CC BY NC 4.0 license.
Figure 13 in Reappraisal and new material of the holotype of Draconyx loureiroi (Ornithischia: Iguanodontia) provide insights on the tempo and modo of evolution of thumb-spiked dinosaurs
Figure 13. Time calibrated Maximum Compatibility Tree (MCT) of the Bayesian clock analysis of the dataset of Xu et al. (2018). Colours of the branches reflect median evolutionary rates and number represents absolute values along branches themselves.
Figure 11 in Reappraisal and new material of the holotype of Draconyx loureiroi (Ornithischia: Iguanodontia) provide insights on the tempo and modo of evolution of thumb-spiked dinosaurs
Figure 11. Pruned strict consensus tree of the parsimony analysis of the dataset of Bell et al. (2018). Bootstrap value in blue, Bremer support in red. Silhouettes from phylopic.org. Credit: Nobu Tamyra, Matthew Dempsey and Gareth Monger.
Figure 10 in Reappraisal and new material of the holotype of Draconyx loureiroi (Ornithischia: Iguanodontia) provide insights on the tempo and modo of evolution of thumb-spiked dinosaurs
Figure 10. Comparison between the left femur ML 434 and the right femur SHN.(JJS).15. Femur SHN.015 and ML 434 in cranial (A, C) and medial (B, D) view. Abbreviations: 4th: fourth trochanter, cr, crest, fh, femoral head, lc, lateral condyle, lt, lesser trochanter, mc, medial condyle, mcl, scar of the Musculus caudifemoralis longus.
Figure 12 in Reappraisal and new material of the holotype of Draconyx loureiroi (Ornithischia: Iguanodontia) provide insights on the tempo and modo of evolution of thumb-spiked dinosaurs
Figure 12. Time calibrated strict consensus tree of the analysis including Draconyx loureiroi in the dataset of Xu et al. (2018) (A). Bootstrap value in blue, Bremer support in red. Red colour is associated with an increasing Homoplasy Concentration index. XY graphs of Average Evolutionary Rates (B) and Average Homoplasy Rates (C) through time. Note the coinciding peaks of both AER and AHR. Silhouettes from phylopic.org. Credit: Michael Keesey, Matthew Dempsey and Pete Buchholz.
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.