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6,175 results for “Composite”
Data from: Flooding and soil composition determine beta-diversity of lowland forests in Northern South America
Beta diversity may be determined by dispersal limitation, environment and phylogeographic history. Our objective was to advance the understanding of plant species turnover in rainforests in Northern South America and determine which factors are affecting species beta-diversity. We evaluated the relative effect of environmental variables (i.e. soil, climate, fragmentation and flooding frequency) and dispersal limitation (i.e. geographical distance and resistance distance due mountain barriers) on tree beta diversity in 32 1-ha lowland forest plots. We found that tree species turnover was better explained by environmental distance than by geographic distance. Although, soil conditions and flooding regime were good predictors of tree species composition, almost half of the variance remained unexplained. In our study system, the Eastern Andean ridge had no significant effect on plant beta diversity, probably because of its young age in relation to the phylogeny. Our results provide support for the importance of environmental factors and suggests a more restricted role of dispersal limitation. Therefore, we advise that conservation strategies of lowland trees should consider specific forest types (e.g. seasonally flooded vs. terra firme, as well as piedmont vs. central Amazonian forests).
Data from: Flowering plant composition shapes pathogen infection intensity and reproduction in bumble bee colonies
<p><span>Pathogens pose significant threats to pollinator health and food security. Pollinators can transmit diseases during foraging, but the consequences of plant species composition for infection is unknown. In agroecosystems, flowering strips or hedgerows are often used to augment pollinator habitat. We used canola as a focal crop in tents, and manipulated flowering strip composition using plant species we had previously shown to result in higher or lower bee infection in short-term trials. We also manipulated initial colony infection to assess impacts on foraging behavior. Flowering strips using high-infection plant species nearly doubled bumble bee colony infection intensity compared to low-infection plant species, with intermediate infection in canola-only tents. Both infection treatment and flowering strips reduced visits to canola, but we saw no evidence that infection treatment shifted foraging preferences. Although high-infection flowering strips increased colony infection intensity, colony reproduction was improved with any flowering strips compared to canola alone. Effects of flowering strips on colony reproduction were explained by nectar availability, but effects of flowering strips on infection intensity were not. Thus, flowering strips benefited colony reproduction by adding floral resources, but certain plant species also come with a risk of increased pathogen infection intensity.</span></p>
Data from: Functional traits and community composition: a comparison among community-weighted means, weighted correlations, and multilevel models
1. Of the several approaches that are used to analyze functional trait-environment relationships, the most popular is community-weighted mean regressions (CWMr) in which species trait values are averaged at the site level and then regressed against environmental variables. Other approaches include model-based methods and weighted correlations of different metrics of trait-environment associations, the best known of which is the fourth-corner correlation method. 2. We investigated these three general statistical approaches for trait-environment associations: CWMr, five weighted correlation metrics (Peres-Neto et al. 2017), and two multilevel models (MLM) using four different methods for computing p-values. We first compared the methods applied to a plant community dataset. To determine the validity of the statistical conclusions, we then performed a simulation study. 3. CWMr gave highly significant associations for both traits, while the other methods gave a mix of support. CWMr had inflated type I errors for some simulation scenarios, implying that the significant results for the data could be spurious. The weighted correlation methods had generally good type I error control but had low power. One of the multilevel models, that from Jamil et al. (2013), had both good type I error control and high power when an appropriate method was used to obtain p-values. In particular, if there was no correlation among species in their abundances among sites, a parametric bootstrap likelihood ratio test (LRT) gave the best power. When there was correlation among species in their abundances, a conditional parametric LRT had correct type I errors but had lower power. 4. There is no overall best method for identifying trait-environment associations. For the simple task of testing, one-by-one, associations between single environmental variables and single traits, the weighted correlations with permutation tests all had good type I error control, and their ease of implementation is an advantage. For the more complex task of multivariate analyses and model fitting, and when high statistical power is needed, we recommend MLM2 (Jamil et al. 2013); however, care must be taken to ensure against inflated type I errors. Because CWMr exhibited highly inflated type I error rates, it should always be avoided. 2. We investigated these three general statistical approaches for trait-environment associations: CWMr, five weighted correlation metrics (Peres-Neto et al. 2017), and two multilevel models (MLM) using five different methods for computing p-values. We first compared the methods applied to a plant community dataset. To determine the validity of the statistical conclusions, we then performed a simulation study. 3. CWMr gave highly significant associations for both traits, while the other methods gave a mix of support. CWMr had inflated type I errors for some simulation scenarios. The weighted correlation methods had generally good type I error control but had low power. One of the multilevel models, that from Jamil et al. (2013), had both good type I error control and high power when an appropriate method was used to obtain p-values. In particular, if there was no correlation among species in their abundances among sites, a parametric bootstrap likelihood ratio test (LRT) gave the best power. When there was correlation among species in their abundances, a conditional parametric LRT had correct type I errors but suffered from low power. 4. There is no overall best method for identifying trait-environment associations. For the simple task of testing, one-by-one, associations between single environmental variables and single traits, the weighted correlations with permutation tests all had good type I error control, and their ease of implementation is an advantage. For the more complex task of multivariate analyses and model fitting, and when high statistical power is needed, we recommend MLM2 (Jamil et al. 2013); however, care must be taken to ensure against inflated type I errors. Because CWMr exhibited highly inflated type I error rates, it should be avoided.
Over 80 years without major disturbance, late successional Białowieża woodlands exhibit complex dynamism, with coherent compositional shifts towards true old‐growth conditions
<p>1. Controversies about successional dynamics of woodland communities have a long history, dating back to the classical debates between Clements and Gleason and continuing into the present. These debates have largely concerned the predictability or convergence of forest developmental trends as well as the relative importance of different mechanisms and forces driving forest succession. However, opportunities for rigorous testing of competing hypotheses are limited, mainly because plot-based studies of forest vegetation spanning more than a decade are scarce and even fewer concern late-successional stands.</p> <p>2. We exploit a unique long-term data set from mesic temperate forests of eastern Poland, spanning ca. 80 years (1936-2012) in strictly protected, late-successional woodlands assigned to seven different 'structural types'. We use non-metric multidimensional scaling to assess stability of species composition over the study period. We examine predictability of composition and change trajectories over time using Mantel statistics, and we examine changes in distributions of dissimilarity indices to assess convergence or divergence at the examined time and spatial scales.</p> <p>3. Tree communities in Białowieża Forest have changed substantially over the last eight decades. Several species (aspen, birch, pine, oak, ash, maple and spruce) exhibited large decreases in density, while few other species (especially hornbeam and lime) have increased in importance across a wide range of initial compositional types. Forest types recognized in earlier periods have become much less distinguishable. Metrics do not yet show clear successional convergence, mainly due to a) declines in the previously broadly distributed spruce and b) persistence of large individuals of intermediate, long-lived species (even though these species lack significant regeneration).</p> <p>4. Synthesis. Late-successional woodland communities of Białowieża Forest are clearly dynamic and do not show quasi-equilibrial properties often assumed of old-growth forests. Forest types previously recognized as distinct have become progressively less differentiated. Plausible explanations invoke alteration in competitive relationships due to complex changes in environment, including climate, N deposition, natural and human disturbance, and ungulate herbivory over 70 years. Hornbeam and lime have been favored over spruce, pine, oak and birch, although the resulting successional convergence is far from complete at this time. In the absence of major disturbance, we expect future decades to show continued and successional homogenization.</p>
Granite composition in Moscow (Havskaya street)
Granite composition "**Russian winter**" or "**Muscovites who died during the bombing**" In 1958, the sculptor and honored art worker Lev Davidovich Muravin created a granite composition, originally called "Russian Winter". Subsequently, the sculpture was renamed, as evidenced by the plate installed in 2009 on its pedestal: "Muscovites who died during the bombing." В 1958 году скульптор и заслуженный деятель искусств Лев Давидович Муравин создал гранитную композицию, изначально называющуюся «Русская зима». Впоследствии скульптура была переименована, о чём свидетельствует установленная в 2009 году на её постаменте табличка: «Москвичам, погибшим при бомбёжках». Model is created by using RealityCapture and Houdini. Source: Objaverse 1.0 / Sketchfab
Clark Hall Composite Cap 20211110
A composite capital rosette and section from Clark Hall, University of Virginia; scanned with iPhone 13 Pro LIDAR sensor using Scaniverse; Source: Objaverse 1.0 / Sketchfab
Composite smoking pipe – "lulka"
ID no.: MAK/S/56/1 Archaeological Museum in Kraków https://muzea.malopolska.pl/en/objects-list/1566 Digitalisation: RDW MIC, Virtual Małopolska project Source: Objaverse 1.0 / Sketchfab
Composite dolmen Spunetam-2 (cross-section)
The dolmen is located on Mezetsu range (Spunetam group of monuments), Tuapse region, Caucasus, Russia, Middle Bronze Age (4000-2000 BC), Dolmen Culture of Caucasus. The stone tomb is placed on the stone cairn with remains of retaining wall. Sepulcher chamber is built with almost wild stone blocks. That is one of the most rare constructions for this culture. Facade wall is absent now. Дольмен расположен на хребете Мезецу, Туапсинский район. Относится к типу составных сооружений. Особенности: дольмен выполнен преимущественно из необработанных блоков, что является редкостью, курган, вероятно, был укреплен крепидой, фасад сейчас отсутсвует. Source: Objaverse 1.0 / Sketchfab
Results of the paper "Composition Identification in Ottoman-Turkish Makam Music Using Transposition-Invariant Partial Audio-Score Alignment"
<p>This repository contains the composition identification and tonic identification results along with the statistical significance values presented in the paper:</p> <p>Şentürk, S., & Serra X. (2016). <strong>Composition Identification in Ottoman-Turkish Makam Music Using Transposition-Invariant Partial Audio-Score Alignment.</strong> In Proceedings of 13th Sound and Music Computing Conference (SMC 2016), (pp. XX–XX)., Hamburg, Germany.</p> <p>Please cite the publication above in any work using this dataset.</p> <p>For the details of the results, please refer to the paper. For any further information please contact the authors.</p> <p>This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.</p>
Food composition database for nutrient intake: selected vitamins and minerals in selected European countries
<p>Following a request from the European Commission for a review of European dietary reference values (DRVs), the EFSA’s Panel on Dietetic Products, Nutrition and Allergies (NDA) has prepared a number of Scientific Opinions on DRVs for micronutrients. The DATA Unit supported this activity by estimating the nutrient intake of a number of micronutrients in nine selected European countries and different age groups. In addition, the DATA Unit also provided information on average content of food sources of the respective nutrients per country based on the composition database, as well as main food group contributors to nutrient intakes and assessed the comparability of the provided data with pertinent published intake data.</p> <p>Intake estimates have been assessed using food consumption data from the EFSA Comprehensive Food Consumption Database (EFSA, 2011a) and the EFSA Nutrient composition database. Food composition data used to populate the Nutrient composition database were provided to EFSA through the EFSA procurement project ‘<em>Updated food composition database for nutrient intake’</em> (Roe at al., 2013). Data were provided following the EFSA specification for standard sample description for food and feed and were classified according to the FoodEx2 classification system of EFSA (EFSA, 2011b).</p> <p>The food composition data used in these assessments and here published cover the following vitamins and minerals: calcium (Ca); copper (Cu); cobalamin (vitamin B12); magnesium (Mg); niacin; phosphorus (P); potassium (K); riboflavin; thiamin; iron (Fe); selenium (Se); vitamin B6; vitamin K, zinc (Zn), and vitamin E<sup>1</sup>. The food composition dataset contains data from seven<sup>2</sup> countries: Finland, France, Germany, Italy, Netherlands, Sweden, and United Kingdom. This dataset version has been checked for outliers but is prior to data completion for missing foods and nutrient values.</p> <p><sup>1</sup> Vitamin E is defined as alpha-tocopherol (AT) only, however as most food composition databases in the EU contain values as alpha-tocopherol equivalents (TE), data on TE are also provided</p> <p><sup>2</sup> For the nutrient intake estimates of Ireland and Latvia present in the opinions of the EFSA Panel on Dietetic Products, Nutrition and Allergies (NDA), food composition data from UK and Germany were respectively used</p>
Vertical Stratification of Peat Pore Water Dissolved Organic Matter composition in a peat bog in Northern Minnesota
<p>Currently peatlands represent a sink for carbon dioxide and source of atmospheric methane. It is unclear the impact that climate change will have on these systems. As such, a large-scale ecosystem manipulation (Spruce and Peatland Responses under Climatic and Environmental Change, SPRUCE) has been implemented at a peat bog (S1 bog) at the Marcel Experimental Forest (MEF), Minnesota, USA, to determine the effects of climatic forcing on ecosystem processes in northern peatlands. In this study, we aimed to: (i) identify peat pore water dissolved organic matter (DOM) composition as a function of depth before the initiation of the manipulation experiment and (ii) contribute to the knowledge of DOM chemistry and decomposition processes at the S1 bog. We found strong vertical resolution in DOM molecular composition and optical properties within the peat column at the S1 bog. Surface samples were dominated by inputs from surface vegetation. The mid-depth, 30-75cm was an area of high reactivity and increased microbial activity with diagenetic formation of many unique compounds such as polycyclic aromatic compounds (PAC) that contain both nitrogen and sulfur heteroatoms. These compounds were previously observed in coal-derived products and were assumed to be responsible for coal’s biological activity. Biological processes taking place at the intermediate depth zone of the peat profile at the S1 bog are assumed to be responsible for the formation of these heteroatomic PAC in our system. Conversely, these compounds might stem from black carbon and nitrogen from potential fires that occurred at the site in the past. Surface and deep DOM exhibited more similar characteristics suggesting the possibility of lateral and vertical advection of pore water from the surface to the deeper horizons. Our results highlight the importance of understanding processes that control DOM production and transformation with depth.</p> <p>Included: FTICR MS data and optical properties data</p>
Composite Embedding Systems Based on DNN-HMM and Attention End-To-End for ZeroSpeech2017 track1 (1)
<p>Deep neural networks (DNNs) were trained for posterior and bottleneck features using Japanese and other language speech data. We explore various DNN types, their combinations, and dimension reduction by principal component analysis (PCA).</p> <p>This version (version 1) extracts DNN bottleneck features obtained from GMM based SAT features. The DNN and GMM were trained by speech data from the corpus of spontaneous Japanese (CSJ).</p>
Composite Embedding Systems Based on DNN-HMM and Attention End-To-End for ZeroSpeech2017 track1 (2)
<p>Deep neural networks (DNNs) were trained for posterior and bottleneck features using Japanese and other language speech data. We explore various DNN types, their combinations, and dimension reduction by principal component analysis (PCA).</p> <p>This version (version 2 ) concatenates CSJ feature vector and PCA compressed feature vector made from attention end-to-end feature.</p> <p>X:CSJ feature (60 dim bottleneck, (version 1 feature))</p> <p>S:Attention end-to-end feature (320 dim)</p> <p>T:PCA(S) (60 dim)</p> <p>Z=concat(X,T)</p>
Seasonal Variation of Thermospheric Composition Observed by NASA GOLD
We examine characteristics of the seasonal variation of thermospheric composition using column number density ratio ∑O/N2 observed by the NASA Global Observations of Limb and Disk (GOLD) mission from low-mid to mid-high latitudes. We found that the ∑O/N2 seasonal variation is hemispherically asymmetric: in the southern hemisphere, it exhibits the well-known annual and seminal pattern, with highs near the equinoxes, and primary and secondary lows near the solstices. In the northern hemisphere, it is dominated by an annual variation, with a minor semiannual component with the highs shifting towards the wintertime. We also found that the durations of the December and June solstice seasons in terms of thermospheric composition are highly variable with longitude. Our hypothesis is that ion-neutral collisional heating in the equatorial ionization anomaly region and auroral Joule heating play substantial roles in this longitudinal dependency.
Dataset for paper "Interpreting the shifts in forest structure, plant community composition, diversity, and functional identity by using remote sensing-derived wildfire severity"
<p>Interpreting the shifts in forest structure, plant community composition, diversity, and functional identity by using remote sensing-derived wildfire severity . New collected data</p>
NCAR/ACOM FTIR Atmospheric Composition Dataset
<p>The NCAR/ACOM Optical Techniques Project operates three high spectral resolution, solar viewing FTIR instruments at Thule, Greenland (76.5ºN, 291.3ºE, 225 masl), Boulder Colorado (40.03ºN, 254.7ºE, 1612 masl) and Mauna Loa Observatory Hawaii (19.5ºN, 204.4ºE, 3396 masl). These instruments operate within the framework of the Network for the Detection of Atmospheric Composition change (NDACC). The raw data are recorded autonomously and downloaded to ACOM servers daily. They are processed at ACOM and produce vertical profiles of several trace atmospheric constituents: O3, HNO3, HCl, HF, CO, N2O, CH4, HCN, C2H6, OCS, H2CO, H2O and ClONO2. These data constitute a long-term reference dataset for tropospheric and stratospheric chemistry investigations.</p> <p>The data, along with metadata and full error analysis are saved to GEOMS conforming HDF files. Per our agreement with NDACC and our sponsor NASA, they are uploaded bi-yearly to the NDACC data handling facility (DHF) at www.ndacc.org. For select species, HDF files are uploaded on a near-real-time basis for the CAMS27 project which use the data for realtime air quality forecasting. Once these data are uploaded they are publicly available. The NDACC has implemented Creative Commons licensing designations for data at the DHF. These data maintain a CC0 license.</p>
dataset for: Carbonate content and stable isotopic composition of atmospheric aerosol carbon in the Canadian High Arctic
<p>Dataset related to publication of the same title in <a href="https://www.atmospheric-chemistry-and-physics.net/">Atmospheric Chemistry and Physics</a></p>
Highly selective hydrogenation of CO2 to propane over GaZrOx/H-SSZ-13 composite
<p>Suppelementary data: Synthesis, testing data, N2 absorption, PXRD, XPS, EDS, TEM, SEM, IR, DFT, TGA, GC-MS, 27Al NMR, source data for graphs (Excel files)</p>
Target-ligand binding affinity from single point enthalpy calculation and elemental composition
<p>This repository contains supporting files for the manuscript entitled: Target-ligand binding affinity from single point enthalpy calculation and elemental composition.</p>
Experimental Investigation of the Bubble Size Distribution in a Mini Plant Batch Bubble Column With Variation of Gas Flux, Bubble Column Height and Composition of the Liquid Phase
<p>This data set contains bubble size distributions (BSD) measured in a dN = 100 mm mini-plant batch bubble column. The BSD were measured using the optical multimode online probe. The liquid holdup, the feed gas volume flow rate/flux, the composition of the liquid phase (water or aqueous solutions of NaCl, EtOH, glycerol or Na2SO3) and the measuring position in the bubble column were varied. </p>
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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.