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1,551 results for “Availability”
Percentage of individuals per size class of available prey for Setophaga petechia gundlachi
<p>Supplemetary materials 3. Percentage of individuals per size class of available prey for <em>Setophaga petechia gundlachi </em>during the reproductive season in Bajo de Santa Ana (n = 159) and Laguna de Cobre-Itabo (n = 813) of Havana, Cuba.</p>
Dataset for Spence et al., "Availability of study protocols for randomized trials published in high-impact medical journals: cross-sectional analysis" (CITATION)
<p>Contains our extraction sheets (as SAS data files), code to calculate the values in the tables in our manuscript, and a supplemental file with additional notes on methods used in our study.</p>
Replication Package for MORCoRA: Multi-Objective Refactoring Recommendation Considering Review Availability
<div> <div>This is the replication package for <em>MORCoRA: Multi-Objective Refactoring Recommendation Considering Review Availability</em></div> <br><br> <div> <p><strong>Refactoring sequences searched by MORCoRA</strong></p> </div> <div>The 6 directories contain the refactoring sequences searched by MORCoRA.</div> <div>The name of each directory is the name of the repository introduced in <em>Table 2. Dataset</em>.</div> <br> <div>Each directory includes 6 CSV files.</div> <div>The name of the CSV file represents the search algorithm used to search refactoring sequences.</div> <br> <div>Note that <em>NsgaiiN</em> represents using the NSGA-II algorithm without considering the review availability objective, which is the RA- in <em>Section 4.5</em>.</div> <br> <div>In each CSV file, a single row is the refactoring sequences searched and the recommended reviewers for it. The sequence with no appropriate reviewers will be noted as <em>No appropriate expertise reviewer</em>.</div> <br><br> <div>In each CSV file, a row consists of multiple columns, the last column represents the recommended reviewer, and the rest columns represent elements in the refactoring sequences.</div> <div>Each element consists of:</div> <div> <ul> <li>ROType: refactoring operation type</li> </ul> </div> <div> <ul> <li>class1info: <em>class1</em> in the <em>Table 1. Refactoring Operations</em> in the paper. It is the information of the source class where the number before <em>#</em> represents the access modifiers according to <a href="https://docs.oracle.com/javase/7/docs/api/constant-values.html#java.lang.reflect.Modifier.PROTECTED">modifiers and their corresponding int values</a>, the name after <em>#</em> represents the name for the class</li> </ul> </div> <div> <ul> <li>class1path: the path to the file containing the class</li> </ul> </div> <div> <ul> <li>class2info: <em>class2</em> in the <em>Table 1. Refactoring Operations</em> the formation of the target class</li> </ul> </div> <div> <ul> <li>class2path: the path to the file containing the class</li> </ul> </div> <div> <ul> <li>target: it can be "class" or "method" or "field" according to the refactoring type. The number before <em>#</em> represents the access modifier. The name after <em>#</em> is the name of the "class" or "method" or "field", and its type is revealed after the <em>@</em> symbol.</li> </ul> </div> <br><br> <div><strong>Manually review results</strong></div> <div>The manual review results of the 60 solutions introduced in <em>Section 4.3</em> is recorded in the <em>manually_review_60_solutions.csv</em></div> <br> <div>It includes 6 columns:</div> <div> <ul> <li>Repository: The name of the repository.</li> </ul> </div> <div> <ul> <li>Recommended Refactoring Operations: the searched refactoring sequence.</li> </ul> </div> <div> <ul> <li>Recommended Reviewer: the reviewer recommended to review the refactoring sequence.</li> </ul> </div> <div> <ul> <li>Reviewable: If no appropriate expertise reviewer is found for the sequence, the value is "0", otherwise "1".</li> </ul> </div> <div> <ul> <li>Code smell Eliminated: The code smell type detected by JDeodorant that the recommended refactoring can eliminate. If the refactoring sequence cannot eliminate any code smell, then it is "No".</li> </ul> </div> <div> <ul> <li>Valid: If the refactoring sequence is recommended with appropriate reviewer (value in the column "Reviewable" is "1") and meaningful, and eliminates at least one code smell, the value is "1", otherwise "0".</li> </ul> </div> </div>
Experimental raw data sets associated with certified reference material BAM-P115 (titanium dioxide) for comparison of nitrogen and argon sorption, available in the universal adsorption information format (AIF)
<p>These data sets serve as models for calculating the specific surface area (BET method) using gas sorption in accordance with ISO 9277.<br>The present measurements were carried out with nitrogen at 77 Kelvin and argon at 87 Kelvin.<br>It is recommended to use the following requirements for the molecular cross-sectional area:<br>Nitrogen: 0.1620 nm²<br>Argon: 0.1420 nm²</p> <p>Expected specific surface area for nitrogen (BET): 140 to 154 m²/g<br>Expected specific surface area for argon (BET): 129 to 135 m²/g</p> <p>Titanium dioxides certified with nitrogen sorption and additionally measured with argon for research purposes were used as sample material.<br>The resulting data sets are intended to serve as comparative data for own measurements and show the differences in sorption behaviour and evaluations between nitrogen and argon.<br>These data are stored in the universal AIF format (adsorption information format), which allows flexible use of the data.</p>
Experimental raw data sets associated with certified reference material BAM-P114 (titanium dioxide) for comparison of nitrogen and argon sorption, available in the universal adsorption information format (AIF)
<p>These data sets serve as models for calculating the specific surface area (BET method) using gas sorption in accordance with ISO 9277.<br>The present measurements were carried out with nitrogen at 77 Kelvin and argon at 87 Kelvin.<br>It is recommended to use the following requirements for the molecular cross-sectional area:<br>Nitrogen: 0.1620 nm²<br>Argon: 0.1420 nm²</p> <p>Expected specific surface area for nitrogen (BET): 24 to 25 m²/g<br>Expected specific surface area for argon (BET): 20 m²/g</p> <p>Titanium dioxides certified with nitrogen sorption and additionally measured with argon for research purposes were used as sample material.<br>The resulting data sets are intended to serve as comparative data for own measurements and show the differences in sorption behaviour and evaluations between nitrogen and argon.<br>These data are stored in the universal AIF format (adsorption information format), which allows flexible use of the data.</p>
Dataset of "Some effects of limited wall-sensor availability on flow estimation with 3D-GANs"
<p>Dataset of the article 'Some effects of limited wall-sensor availability on flow estimation with 3D-GANs' (https://doi.org/10.1007/s00162-024-00718-w). The codes processing data here are on https://github.com/erc-nextflow/3D-GAN.</p> <p>This project has received funding from the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation programme (grant agreement no. 949085, NEXTFLOW). Views and opinions expressed are, however, those of the authors only, and do not necessarily reflect those of the European Union or the ERC. Neither the European Union nor the granting authority can be held responsible for them. A.C.M. acknowledges financial support from the Spanish Ministry of Universities under the Formación de Profesorado Universitario (FPU) programme 2020.</p>
Data Set available for Liquid Biopsy of CML Diagnosis
<p><em><span>Chronic Myeloid Leukemia, CML, is caused in patients with myeloproliferative disorders by the presence of BCR::ABL1. The research discussed the integration of microfluidic chips with biosensors for the purpose of detecting biomarkers in peripheral blood thereby showing the raw experimental data set avaialble, liquid bipsy sample set available and Calculation for methods and data Simulation along with graphs, which could obviate the need for painful biopsies, thereby improving diagnostic accuracy and accessibility.</span></em></p>
Annex B – Occurrence data on brominated phenols and their derivatives in food submitted to EFSA, dietary surveys per country and age group available in the EFSA Comprehensive Database considered in the exposure assessment, and the detailed results of the chronic dietary exposure assessment to 2,4,6-TBP and the contribution of different food groups to the dietary exposure
<p>This Annex contains the occurrence data submitted to EFSA, the dietary surveys per country and age group, and the detailed results of the chronic dietary exposure assessment to 2,4,6-TBP and the contribution of different food groups to the dietary exposure related to the Update of the risk assessment of brominated phenols and their derivatives in food.</p>
Uncovering Hidden Inefficiencies in the Route Availability Document
Open the record for dataset details and reuse information.
Unlocking higher methane yields and digestate nitrogen availability in soil through thermal treatment of feedstocks in a two-step anaerobic digestion- Dataset
<p>This is a data set for the article "<span>Unlocking higher methane yields and digestate nitrogen availability in soil through thermal treatment of feedstocks in a two-step anaerobic digestion", published in Chemical and Biological Technologies in Agriculture journal.</span></p>
Idiothetic representations are modulated by availability of sensory inputs and task-demands in hippocampal-septal circuit
<p>This is the dataset underlying the results presented in the article titled: "Idiothetic representations are modulated by availability of sensory inputs and task-demands in hippocampal-septal circuit". Data is sub-divided per brain regions: CA1, CA3, and lateral septum (LS). Then each region is subdivided by mouse number, and finally by experiment (day). Each experiment contains two main files: ms.mat (miniscope data) and behav.mat (behavior data). These two streams are not sampled at the same frequency and should thus be interpolated during analysis (timestamps are available for both streams). Each .mat files can be opened with Matlab or with any HDF5 reader (e.g. in H5py Python).</p>
Data from: Centennial-scale reductions in nitrogen availability in temperate forests of the United States
Forests cover 30% of the terrestrial Earth surface and are a major component of the global carbon (C) cycle. Humans have doubled the amount of global reactive nitrogen (N), increasing deposition of N onto forests worldwide. However, other global changes—especially climate change and elevated atmospheric carbon dioxide concentrations—are increasing demand for N, the element limiting primary productivity in temperate forests, which could be reducing N availability. To determine the long-term, integrated effects of global changes on forest N cycling, we measured stable N isotopes in wood, a proxy for N supply relative to demand, on large spatial and temporal scales across the continental U.S.A. Here, we show that forest N availability has generally declined across much of the U.S. since at least 1850 C.E. with cool, wet forests demonstrating the greatest declines. Across sites, recent trajectories of N availability were independent of recent atmospheric N deposition rates, implying a minor role for modern N deposition on the trajectory of N status of North American forests. Our results demonstrate that current trends of global changes are likely to be consistent with forest oligotrophication into the foreseeable future, further constraining forest C fixation and potentially storage.
Water availability influences thermal safety margins for leaves
<p>One application of plant physiological heat tolerance measurements is the assessment of vulnerability to increasing environmental temperatures under climatic change. A thermal safety margin, the difference between physiological tolerance and environmental temperature, is a common metric for the assessment of plant thermal vulnerability. However, there are biological and methodological aspects to consider when evaluating thermal vulnerability that have the potential to substantially alter assessments. Two such aspects include the leaf to air temperature relationship and the scale at which air temperature data are collected.</p> <p>We grew plants of a desert species, Myoporum montanum, in situ under water- stressed and well-watered conditions, measured their leaf temperatures and photosynthetic heat tolerance (T<sub>50</sub> threshold) every third day over 12 days in summer. Thermal safety margins were calculated based on leaf temperatures and compared to those calculated with local and regional air temperatures.</p> <p>We found that heat tolerance and the thermal vulnerability assessment of a plant changed with water status. When water was readily available, plants maintained wide leaf temperature safety margins and displayed partial-homeothermy. When cooling via transpiration was limited, increasing leaf temperature corresponded with occurrences of leaf poikilo- and megathermy, higher heat tolerance, and narrower safety margins.</p> <p>Our study shows high physiological heat thresholds are not necessarily reflective of wide safety margins, but instead can indicate a greater vulnerability and increased risk of heat stress exposure. Calculating thermal safety margins using air temperatures can also substantially alter margin widths. Where possible, the use of leaf temperatures in assessments of thermal vulnerability will lead to more meaningful vulnerability assessments. We recommend considering the source and temporal pairing of temperature measurements as well as plant water status, when measuring and interpreting plant thermal safety margins.</p>
Win some, lose some: mesocosm communities maintain community productivity despite lower phosphorus availability because of increased species diversity
<p><u>Aims</u><br> The restoration of degraded ecosystems typically focuses on establishing assemblages of target species, but successful recovery should also be evaluated by the ecosystem's functioning to guarantee long-term persistence. We investigated how the processes underlying community assembly (i.e. species loss, species gain and changes in abundance of resident species) influenced ecosystem functioning in experimental grassland communities in different restoration states.</p> <p><u>Location </u><br> A greenhouse experiment in Northern Flanders, Belgium.</p> <p><u>Methods</u><br> We set up a mesocosm experiment with communities of nineteen planted species, ranging from slow-growing species from poorly productive <i>Nardus</i> grasslands to fast-growing species from highly productive <i>Lolium perenne</i> grasslands. We categorized the mesocosms into different grassland restoration states based on known abiotic and biotic restoration barriers for semi-natural grassland restoration: soil phosphorus levels and soil biota communities. After two growing seasons, we used the CAFE approach, an ecological application of the Price equation, to partition the effects of plant community assembly on ecosystem functioning (here community productivity) for the different restoration states.</p> <p><u>Results</u><br> Adding soil biota communities sampled from reference <i>Nardus</i> grasslands versus more intensively managed grasslands did not have a significant effect on either plant species richness or biomass productivity. Lower soil phosphorus concentrations (i.e. abiotic restoration) resulted in a higher plant species richness. However, the net effect on productivity was close to zero. The increase in productivity caused by species gains was compensated through decreases in productivity caused by species loss and by decreases in the abundance or functioning of species that are present in both abiotically degraded and abiotically restored states.</p> <p><u>Conclusions</u><br> Not only species richness but also species identity resulted in changes in ecosystem functioning (i.e. productivity), even though the net functional effects were close to zero. More specifically, we found that species richness-driven increases in productivity were counterbalanced by resource-driven and species identity-driven reductions in productivity.</p>
Appendix B: Language Corpora Available for Text Mining
<p>Appendix B is associated with <em><strong>Chapter 3: Text Pre-Processing</strong></em> of the book -- Manika Lamba and Margam Madhusudhan (2021) Text Mining for Information Professionals: An Uncharted Territory, SpringerNature.</p>
Appendix-A: Online Repositories Available for Text Mining
<p>Appendix A is associated with Chapter 2: Text data and where to find them of the book: Manika Lamba and Margam Madhusudhan (2021) Text Mining for Information Professionals: An Uncharted Territory, SpringerNature.</p>
PubMed inner references obtained from five freely available bibliographic data sources
<p>This dataset contains PMID-to-PMID citations of PubMed 2020 Baseline extracted from five freely available bibliographic data sources (COCI, Dimensions, MAG, NIH-OCC, and S2ORC).</p> <p>Each line contains one citing PubMed document and its cited references. The citing and cited documents are separated by a tab (\t) and the cited references are separated by a semicolon (;).</p>
Mycorrhizal effects on decomposition and soil CO2 flux depend on changes in nitrogen availability during forest succession
<p>Mycorrhizal fungi play a central role in plant nutrition and nutrient cycling, yet our understanding on their effects on free-living microbes, soil carbon (C) decomposition and soil CO2 fluxes remains limited.</p> <p>Here we used trenches lined with mesh screens of varying sizes to isolate mycorrhizal hyphal effects on soil C dynamics in subtropical successional forests.</p> <p>We found that the presence of mycorrhizal hyphae suppressed soil CO2 fluxes by 17% in early-successional forests, but enhanced CO2 losses by 20% and 32% in mid- and late-successional forests, respectively. The inhibitory effects of mycorrhizal fungi on soil CO2 fluxes in the young stands were associated with changes in soil nitrogen (N) mineralization and microbial activities, suggesting that competition between mycorrhizae and saprotrophs for N likely suppressed soil C decomposition. In the mid- and late-successional stands, mycorrhizal enhancement of CO2 release from soil likely resulted from both hyphal respiration and mycorrhizal-induced acceleration of organic matter decay.</p> <p>Synthesis. Our results highlight the sensitivity of mycorrhizal fungi-saprotroph interactions to shifts in nutrient availability and demand, with important consequences for soil carbon dynamics particularly in ecosystems with low nutrient conditions. Incorporating such interactions into models should improve the simulations of forest biogeochemical cycles under global change.</p>
Data and Code for Atmospheric oxygen abundance, marine nutrient availability, and organic carbon fluxes to the seafloor
<p>Code and Data for manuscript "<strong>Atmospheric oxygen abundance, marine nutrient availability, and organic carbon fluxes to the seafloor"</strong></p>
Data from: Resource availability affects seasonal trajectories of population-level learning
<p>Environmental effects on learning are well known, such as cognition that is mediated by nutritional consumption. Less known is how seasonally variable environments affect phenological trajectories of learning. Here, we test the hypothesis that nutritional availability affects seasonal trajectories of population-level learning in species with developmentally plastic cognition. We test this in bumble bees (Apidae: Bombus), a clade of eusocial insects that produce individuals at different time points across their reproductive season and exhibit organ developmental plasticity in response to nutritional consumption. To accomplish this, we develop a theoretical model that simulates learning development across a reproductive season for a colony parameterized with observed life history data. Our model finds two qualitative seasonal trajectories of learning: (1) an increase in learning across the season and (2) no change in learning across the season. We also find these two qualitative trajectories revealed by empirical learning data; the proportion of workers successfully completing a learning test increases across a season for two bumble bee species (Bombus auricomus, Bombus pensylvanicus), but does not change for another three (Bombus bimaculatus, Bombus griseocollis, Bombus impatiens). This study supports the novel consideration that resources affect seasonal trajectories of population-level learning in species with developmentally plastic cognition.</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.