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11,506 results for “Dynamics”
Impacts of anthropogenic management legacies on forest dynamics of the Tibetan Plateau transition region under changing climates
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Fig. 2 in Population dynamics and predatory impact of the alien jellyfish Aurelia solida (Cnidaria, Scyphozoa) in the Bizerte Lagoon (southwestern Mediterranean Sea) Abstract
Fig. 2: Seasonal variation of (A) abiotic factors (temperature and salinity), (B) zooplankton abundance and chlorophyll biomass, and (C) zooplankton composition in Bizerte Lagoon between November 2012 and August 2014.
Searching for the relationship between the presence, extent, location and 12-month dynamics of cardiac fibrosis and the genetic profile in patients with dilated cardiomyopathy - a pilot study
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Effect of pre-twinning on deformation behavior of [0001]-textured nanocrystalline Mg: a molecular dynamics study
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The 2023 Mw 6.0 Jishishan Earthquake: A Slow Unilateral Rupture on a Blind Thrust Fault Revealed by High-Precision Earthquake Detection, Location, and Dynamic modeling
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Fig. 2 in Ancyrophora gracilis L , 1892 and Actinocephalus permagnus Wellmer, 1910 (Eugregarinorida: Apicomplexa) in natural populations of ground beetles (Coleoptera, Carabidae) - hosts preferences, intensity and seasonal dynamic
Fig. 2. Mean density of Actinocephalus permagnus (AT) and Ancyrophora gracilis (AC) in relation to habitat. Circle – woodland, square – meadow, triangle – arable land
Supplement notebooks for "scBoolSeq: Linking scRNA-Seq Statistics and Boolean Dynamics"
<p>See https://github.com/bnediction/scBoolSeq-supplementary</p>
Dynamicity of Hydrologic Function
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Supporting data for "Health benefits of US light-duty vehicle electrification: roles of fleet dynamics, clean electricity, and policy timing"
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FIGURE 8 in Morphospace dynamics and intraspecies variety of Sorex araneus and S. tundrensis according to recent and fossil data
FIGURE 8. Results of PCA based on the combined 'Fossil/Recent' datasets of m1 shape. A, m1 morphospace of PC1-2. B1, inset with the relationships between samples and single specimens of S. tundrensis based on the m1 set. B2, Similar inset with data of S. araneus. Key: a, re-defined specimens of S. araneus (to S. tundrensis: Sim3, S18 and S19); line 'Cher 1,' association of fossil specimens of S. araneus from Cher1 locality; hatched area displays the overall convex hull of Dan' S. tundrensis subsample;line 'Sim3,' association of fossil specimens of S. araneus from Sim3 locality; see also Figure 5.
AlphaFold2 Modeling and Molecular Dynamics Simulations of the Conformational Ensembles for the SARS-CoV-2 Spike Omicron JN.1, KP.2 and KP.3 Variants : Mutational Profiling of Binding Energetics Reveals Epistatic Drivers of the ACE2 Affinity and Escape Hotspots of Antibody Resistance
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Raw plasmon ruler data of conformational dynamics of Hsp90
<p>Four time series from Plasmon ruler experiments<br>time resolution 0.1 s.<br>total length 6 h<br>Hsp90 concentration 240 pM<br>First analyzed and published 2018 in: https://pubs.acs.org/doi/10.1021/acs.nanolett.8b03342</p> <p>2024 analyzed for memory in conformational dynamics in: https://arxiv.org/abs/2404.16799</p>
FIGURE 2 in Computational fluid dynamics modeling of fossil ammonoid shells
FIGURE 2. All of the shells employed in this study plotted in Westermann morphospace. The 3D models used for each member are shown to the right of the name/designation in the legend. Cardioceras, Oppelia, and Sphenodiscus are based on the shells employed in Jacobs (1992), Nautilus pompelius was created using laser scans and scaled to two different sizes (life-size [approx. 14.5 cm] and 5 cm diameter), and all other shells were created to match basic Westermann morphotypes (Westermann, 1996; Ritterbush and Bottjer, 2012).
FIGURE 7 in Adjustments in population and reproductive dynamics of native and non-native congeneric species during 26 years after invasion
FIGURE 7 | Estimated mean lengths at first maturity (L50) for both Serrasalmus marginatus (A and C, non-native) and S. maculatus (B and D, native) piranha species for each sex and each sampled timeperiod in the upper Paraná River floodplain (continuous black line: 1986–1988, first time-period; dashed red line: 2000–2002, second time-period; dotted blue line: 2010–2012, third time-period).
FIGURE 5 in Adjustments in population and reproductive dynamics of native and non-native congeneric species during 26 years after invasion
FIGURE 5 | Mortality rates of both non-native (left) and native (right) species for each sampled timeperiod in the upper Paraná River floodplain. White dots: ages that were not used for the estimated mortality. Black dots: ages used for the estimated mortality. Grey dashed line: confidence intervals. A. and B. 1986–1988: first time-period; C. and D. 2000–2002: second time-period; E. and F. 2010–2012: third time-period.
FIGURE 2 in Adjustments in population and reproductive dynamics of native and non-native congeneric species during 26 years after invasion
FIGURE 2 | Temporal trends in abundance of both non-native (left) and native species (right) in each habitat. CPUE values were log(x+1) transformed to decrease extreme values.
FIGURE 4 in Adjustments in population and reproductive dynamics of native and non-native congeneric species during 26 years after invasion
FIGURE 4 | Frequency distribution of age classes by time-period of both non-native and native species in the upper Paraná River floodplain. Dashed line: median; dotted line: lower and upper quartiles.
Рис. 4. Àинамика гибеΛи гусениц коΛьчатого шеΛкопряΔа, собранных в районе УПН, соΔержащихся в Λабораторных усΛовиях. ВертикаΛьно: коΛичество погибших гусениц (% от чисΛа собранных за весь периоΔ иссΛеΔований в 2019 г. гусениц). ГоризонтаΛьно: Δата осмотра в Λаборатории. В правом верхнем угΛу графика: Δата сбора гусениц в районе УПН. — гибеΛь от вируса яΔерного поΛиэΔроза; — гибеΛь от бактериоза Fig. 4. Dynamics of death of the Lackey moth caterpillars collected at the SOM and kept in the laboratory, 2019. Vertical: number of deaths (percentage from the total number of caterpillars collected in 2019 (578 caterpillars)); horizontal: dates of laboratory controls. Upper right corner: collection date. — death from NPV; — death from bacteriosis in Lackey Moth (Malacosoma Neustria L., Lasiocampidae, Lepidoptera) Population During The Eruptive Phase
Рис. 4. Àинамика гибеΛи гусениц коΛьчатого шеΛкопряΔа, собранных в районе УПН, соΔержащихся в Λабораторных усΛовиях. ВертикаΛьно: коΛичество погибших гусениц (% от чисΛа собранных за весь периоΔ иссΛеΔований в 2019 г. гусениц). ГоризонтаΛьно: Δата осмотра в Λаборатории. В правом верхнем угΛу графика: Δата сбора гусениц в районе УПН. — гибеΛь от вируса яΔерного поΛиэΔроза; — гибеΛь от бактериоза Fig. 4. Dynamics of death of the Lackey moth caterpillars collected at the SOM and kept in the laboratory, 2019. Vertical: number of deaths (percentage from the total number of caterpillars collected in 2019 (578 caterpillars)); horizontal: dates of laboratory controls. Upper right corner: collection date. — death from NPV; — death from bacteriosis
Development of public dynamic spatio-temporal monitoring and analysis tool of supply chain vulnerability, resilience, and sustainability
<p>Supply chains play a pivotal role in driving economic growth and societal well-being, facilitating the efficient movement of goods from producers to consumers. However, the increasing frequency of disruptions caused by geopolitical events, pandemics, natural disasters, and shifts in commerce poses significant challenges to supply chain resilience. This draft update report discusses the development of a dynamic spatio-temporal monitoring and analysis tool to assess supply chain vulnerability, resilience, and sustainability. Leveraging news data, macroeconomic metrics, inbound cargo data (for sectors in California), and operational conditions of California's highways, the tool employs Natural Language Processing (NLP) and empirical regression analyses to identify emerging trends and extract valuable information about disruptions to inform decision-making. Key features of the tool include sentiment analysis of news articles, topic classification, visualization of geographic locations, and tracking of macroeconomic indicators. By integrating diverse and dynamic data sources (e.g., news articles) and using empirical and analytical techniques, the tool offers a comprehensive framework to enhance our understanding of supply chain vulnerabilities and resilience, ultimately contributing to more effective strategies for decision-making in supply chain management. The dynamic nature of this tool enables continuous monitoring and adaptation to evolving conditions, thereby enhancing the analysis of resilience and sustainability in global supply chains.</p>
Monetary policy shock, external macroeconomic shocks and the domestic output dynamics in Ethiopia: an SVAR approach
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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.