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4,486 results for “emergence”
Fig. 1 in Polyclinum constellatum (Tunicata, Ascidiacea), an emerging non-indigenous species of the Mediterranean Sea: integrated taxonomy and the importance of reliable DNA barcode data Abstract
Fig. 1: Map of the Mediterranean Sea showing the literature records (black rhombuses) of P. constellatum and the new findings (red dots).
Dataset: Vanguard Emerging Markets Government Bond Index Fund (VWOB) Stock Performance
This dataset provides historical stock market performance data for specific companies. It enables users to analyze and understand the past trends and fluctuations in stock prices over time. This information can be utilized for various purposes such as investment analysis, financial research, and market trend forecasting.
Dataset: VictoryShares Emerging Markets Value Momentum ETF (UEVM) Stock Performance
This dataset provides historical stock market performance data for specific companies. It enables users to analyze and understand the past trends and fluctuations in stock prices over time. This information can be utilized for various purposes such as investment analysis, financial research, and market trend forecasting.
Dataset: First Trust Emerging Markets Equity Select ETF (RNEM) Stock Performance
This dataset provides historical stock market performance data for specific companies. It enables users to analyze and understand the past trends and fluctuations in stock prices over time. This information can be utilized for various purposes such as investment analysis, financial research, and market trend forecasting.
Dataset: First Trust RiverFront Dynamic Emerging Markets ETF (RFEM) Stock Performance
This dataset provides historical stock market performance data for specific companies. It enables users to analyze and understand the past trends and fluctuations in stock prices over time. This information can be utilized for various purposes such as investment analysis, financial research, and market trend forecasting.
Dataset: Invesco Dorsey Wright Emerging Markets Momentum ETF (PIE) Stock Performance
This dataset provides historical stock market performance data for specific companies. It enables users to analyze and understand the past trends and fluctuations in stock prices over time. This information can be utilized for various purposes such as investment analysis, financial research, and market trend forecasting.
Dataset: National Security Emerging Markets Index ETF (NSI) Stock Performance
This dataset provides historical stock market performance data for specific companies. It enables users to analyze and understand the past trends and fluctuations in stock prices over time. This information can be utilized for various purposes such as investment analysis, financial research, and market trend forecasting.
Dataset: Matthews Emerging Markets Discovery Active ETF (MEMS) Stock Performance
This dataset provides historical stock market performance data for specific companies. It enables users to analyze and understand the past trends and fluctuations in stock prices over time. This information can be utilized for various purposes such as investment analysis, financial research, and market trend forecasting.
Dataset: iShares Emergent Food and AgTech Multisector ETF (IVEG) Stock Performance
This dataset provides historical stock market performance data for specific companies. It enables users to analyze and understand the past trends and fluctuations in stock prices over time. This information can be utilized for various purposes such as investment analysis, financial research, and market trend forecasting.
Data from: Machine learning without a processor: Emergent learning in a nonlinear analog network
<p>The capabilities of digital artificial neural networks grow rapidly with their size, however the time and energy required to train them does as well. The tradeoff is far better for Brains, where the constituent parts (neurons) update their analog connections in ignorance of the actions of other neurons, eschewing centralized processing. Recently introduced analog electronic <em>contrastive local learning networks </em>(CLLNs) share this important decentralized property. However their capabilities were limited because existing implementations are linear. In this dataset we include experimental demonstrations of a nonlinear CLLN, establishing a new paradigm for scalable learning. Included here are data and scripts required to generate figures 2-6 of the manuscript titled "Machine learning without a processor: Emergent learning in a nonlinear analog network".</p>
HYBRID WARFARE AS A PHENOMENON: EMERGENCE AND DEFINITIONAL PROBLEMS
<p><span>The article analyzes the problems of the emergence of the phenomenon of hybrid warfare. Different approaches to the definition of this category in domestic and foreign scientific literature are considered. The key theoretical concepts for the interpretation of the term hybrid warfare are formulated. A number of distinctive features in the general characterization of the phenomenon of hybrid warfare are given.</span></p>
Figure 5 in Fish domestication in aquaculture: reassessment and emerging questions
Figure 5. – Evolution of aquaculture production since 1950 of Japanese amberjack Seriola quinqueradiata (A), common carp Cyprinus carpio (B), Nile tilapia Oreochromis niloticus (C), and Atlantic salmon Salmo salar (D) (based on the FAO database).
Figure 2 in Fish domestication in aquaculture: reassessment and emerging questions
Figure 2. – Evolution of marine capture fisheries since 1950 of Atlantic cod Gadus morhua (A), blue whiting Micromesistius poutassou (B), orange roughy Hoplostethus atlanticus (C), and skipjack tuna Katsuwonus pelamis (D) (based on the FAO database).
Data from: Sequence-based detection of emerging antigenically novel influenza A viruses
<p>The detection of evolutionary transitions in influenza A (H3N2) viruses' antigenicity is a major obstacle to effective vaccine design and development. In this study, we describe NIAViD, an unsupervised machine learning tool, adept at identifying these transitions, using HA1 sequence and associated physicochemical properties. NIAViD, performed with 88.9% (95% CI, 56.5%–98.0%) and 72.7% (95% CI,43.4%– 90.3%) sensitivity in training and validation respectively, outperforming the uncalibrated null model – 33.3% (95% CI,12.1%–64.6%) and does not require the need for potentially biased, time-consuming and costly laboratory assays. The pivotal role of Boman's index, indicative of the virus's cell surface binding potential, is underscored, enhancing the precision of detecting antigenic transitions. NIAViD's efficacy is not only in identifying influenza isolates that belong to novel antigenic clusters, but also in pinpointing potential sites driving significant antigenic changes, without the reliance on explicit modeling of hemagglutinin inhibition titers. Our approach holds immense promise to augment existing surveillance networks, offering timely insights for the development of updated, effective influenza vaccines. Consequently, NIAViD, in conjunction with other resources, could be used to support surveillance efforts and inform the development of updated influenza vaccines.</p>
Рис. 3. Platarctia ornata: 1–4 — имаго, виΑ сверху (1, 2 — самцы; 3, 4 — самки); 5–10 — гусеницы сеΑьмого возраста (5, 6 — форма с черными и рыжими воΛосками; 7, 8 — форма с рыжими воΛосками; 9, 10 — форма с черными воΛосками); 11 — кокон; 12–14 — кукоΛка; 15 — неΑавно отроΑившийся самец. 5, 7, 9, 13 — виΑ сбоку; 6, 8, 10, 14 — виΑ сверху; 12 — виΑ снизу. Δанные сбора имаго: 1 — Буреинский заповеΑник, 4 км В корΑона «Новый МеΑвежий», 1400 м наΑ ур. м., 24.06.2014; 2, 3 — Буреинский заповеΑник, корΑон «Новый МеΑвежий», ex pupa 12–13.09.2018; 4 — там же, 4.07.2018 Fig. 3. Platarctia ornata: 1–4 — imago, dorsal view (1, 2 — males; 3, 4 — females); 5–10 — seventh instar larvae (5, 6 — with black and red hairs; 7, 8 — with red hairs; 9, 10 — with black hairs only); 11 — cocoon; 12–14 — pupа; 15 — newly emerged male. 5, 7, 9, 13 — lateral view; 6, 8, 10, 14 — dorsal view; 12 — ventral view. Data labels for imago insects: 1 — Bureinsky State Nature Reserve, 4 km E Novyi Medvezhii cordon, 1400 m above sea level, 24.06.2014; 2, 3 — Bureinsky State Nature Reserve, Novyi Medvezhii cordon, ex pupa 12–13.09.2018; 4 — same location, 4.07.2018 in Moths (Lepidoptera, Macroheterocera, Excluding Geometridae And Noctuidae S.L.) Of The Bureinsky State Nature Reserve And Adjacent Territories (Khabarovsk Krai, Russia)
Рис. 3. Platarctia ornata: 1–4 — имаго, виΑ сверху (1, 2 — самцы; 3, 4 — самки); 5–10 — гусеницы сеΑьмого возраста (5, 6 — форма с черными и рыжими воΛосками; 7, 8 — форма с рыжими воΛосками; 9, 10 — форма с черными воΛосками); 11 — кокон; 12–14 — кукоΛка; 15 — неΑавно отроΑившийся самец. 5, 7, 9, 13 — виΑ сбоку; 6, 8, 10, 14 — виΑ сверху; 12 — виΑ снизу. Δанные сбора имаго: 1 — Буреинский заповеΑник, 4 км В корΑона «Новый МеΑвежий», 1400 м наΑ ур. м., 24.06.2014; 2, 3 — Буреинский заповеΑник, корΑон «Новый МеΑвежий», ex pupa 12–13.09.2018; 4 — там же, 4.07.2018 Fig. 3. Platarctia ornata: 1–4 — imago, dorsal view (1, 2 — males; 3, 4 — females); 5–10 — seventh instar larvae (5, 6 — with black and red hairs; 7, 8 — with red hairs; 9, 10 — with black hairs only); 11 — cocoon; 12–14 — pupа; 15 — newly emerged male. 5, 7, 9, 13 — lateral view; 6, 8, 10, 14 — dorsal view; 12 — ventral view. Data labels for imago insects: 1 — Bureinsky State Nature Reserve, 4 km E Novyi Medvezhii cordon, 1400 m above sea level, 24.06.2014; 2, 3 — Bureinsky State Nature Reserve, Novyi Medvezhii cordon, ex pupa 12–13.09.2018; 4 — same location, 4.07.2018
Fig. 2 in Parasitism and emergence of Tetrastichus howardi (Hymenoptera: Eulophidae) on Diatraea saccharalis (Lepidoptera: Crambidae) larvae, pupae and adults
Fig. 2. Larvae, pupae and adults of Tetrastichus howardi (Hymenoptera: Eulophidae) in pupae of Diatraea saccharalis(Lepidoptera: Crambidae) (A, B, C); D. saccharalis adult parasitized by T. howardi (D).
Fig. 1 in Infection of Anastrepha ludens (Diptera: Tephritidae) adults during emergence from soil treated with Beauveria bassiana under various texture, humidity, and temperature conditions
Fig. 1. Adult mortality of Anastrepha ludens infected with different concentrations of Beauveria bassiana conidia, afer emerging from treated soil. Different letters indicate significant differences among treatments based on 1-way ANOVA followed by the Tukey Honest Significant Difference test, P <0.05).
Fig. 2 in Post-harvest crop destruction effects on picture-winged fly (Diptera: Ulidiidae) emergence
Fig. 2. Spring trial mean (± SE) adult silk fly emergence from soil within cages erected over the treatment plots where plants were plowed, disked twice (2x), or lef standing.
Fig. 1 in Post-harvest crop destruction effects on picture-winged fly (Diptera: Ulidiidae) emergence
Fig. 1. Fall trial mean (± SE) adult silk fly emergence from soil within cages erected over the treatment plots where plants were disked once (1x), disked twice (2x), mowed, or lef standing.
CESM2 data for "Internal Wind Driven Ocean Circulation Variability Delays the Time of Emergence of Externally Forced Sea Surface Temperature Trends" - submitted to GRL
<p>CESM2 Experiment names:</p> <ul> <li>MDM = mechanically decoupled model (referred to as MDM in paper)</li> <li>FCM = fully coupled model (referred to as FCM in paper)</li> </ul> <p>Details for files cesm2.[experiment name].SST.noise.nc</p> <ul> <li>These files include the unfiltered time-varying SST noise </li> <li>"noise" refers to ensemble standard deviation (no 10-yr running mean has been applied) </li> <li>"SST" is the annual mean SST</li> <li>Time period is 1900-2014</li> </ul> <p>For the ensemble mean SST, see previously created Zenodo repository by Fu et al: https://zenodo.org/records/10484207</p> <p>For other ensemble mean variables, see previously created Zenodo repository by McMonigal et al: https://zenodo.org/records/7154374</p>
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.