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599 results for “Volatile”
Raw data for "A-Proof-of -Concept: In vivo Volatile Organic Compounds Secretion Monitoring as a Tool for Prediction of Natural Pest Control Ability"
<p>This upload refers to work entitled "A-Proof-of -Concept: In vivo Volatile Organic Compounds Secretion Monitoring as a Tool for Prediction of Natural Pest Control Ability" and contains the unprocessed data obtained during experiments perform. </p>
A Survival Analysis based Volatility and Sparsity Modeling Network for Student Dropout Prediction
<p>KDDCup15.rar and XuetangX.rar are the metadata used in the paper "A Survival Analysis based Volatility and Sparsity ModelingNetwork for Student Dropout Prediction". Both of them have be drawn from the largest MOOC platform in China, XuetangX (see https://www.xuetangx.com/). If any interested parties want to fetch the original dataset, they may follow the URLs bellow:</p> <p>KDDCup 2015 dataset is available at <a href="https://www.biendata.xyz/competition/kddcup2015/data/">https://www.biendata.xyz/competition/kddcup2015/data/</a>.</p> <p>XuetangX dataset is available at <a href="http://moocdata.cn/data/user-activity">http://moocdata.cn/data/user-activity</a>.</p>
Effect of experimental flour preparation and thermal treatment on the volatile properties of aqueous chickpea flour suspensions
<p>Final data used for figures in the paper: Noordraven, L. E., Buvé, C., Grauwet, T., & Van Loey, A. M. (2022). Effect of experimental flour preparation and thermal treatment on the volatile properties of aqueous chickpea flour suspensions. <em>LWT</em>, 113171.</p>
Testing what we know about coffee volatiles affecting behaviour of Hypothenemus hampei
<p>Raw data about laboratory and field assays of volatile compounds that affects coffee berry borer, <em>Hypothenemus hampei.</em></p>
Volatile social environments can favour investments in quality over quantity of social relationships
<p>Cooperation does not occur in a vacuum: interactions develop over time in social groups that undergo demographic changes. Intuition suggests that stable social environments favour developing few but strong reciprocal relationships (a 'focused' strategy), while volatile social environments favour the opposite: more but weaker social relationships (a 'diversifying' strategy). We model reciprocal investments under a quality-quantity tradeoff for social relationships. We find that volatility, counterintuitively, can favour a focused strategy. This result becomes explicable through applying the theory of antagonistic pleiotropy, originally developed for senescence, to social life. Diversifying strategies show superior performance later in life, but with costs paid at young ages while the social network is slowly being built. Under volatile environments, many individuals die before reaching sufficiently old ages to reap the benefits. Social strategies that do well early in life are then favoured: a focused strategy leads individuals to form their first few social bonds quickly and to make strong use of existing bonds. Our model highlights the importance of pleiotropy and population age structure for the evolution of cooperative strategies and other social traits, and shows that it is not sufficient to reflect on the fate of survivors only, when evaluating the benefits of social strategies.</p>
Pre-Analysis Bioinformatics Files for The Microbiome and Volatile Organic Compounds Reflect the State of Decomposition in an Indoor Environment
<p>Data statistics before and after trimming, FastQC reports before and after trimming, MultiQC reports before and after trimming, commands for the Kraken2-Bracken analysis, and classification reports. Read the read.me file for file names and descriptions. </p>
Leaf flammbility and volatiles of Ginkgo, Agathis, and Dicksonia
<p>The Triassic-Jurassic Boundary marks the third largest mass extinction event in the Phanerozoic, characterised by a rise in CO<sub>2</sub>-concentrations from ~600 ppm to ~2100 – 2400ppm, coupled with a ~3.0 – 4.0°C temperature rise. This is hypothesized to have induced major floral turnover, altering vegetation structure, composition and leaf morphology, which in turn are hypothesized to have driven changes in wildfire. However, the effects of elevated CO<sub>2</sub> on fuel properties, such as chemical composition of leaves, are also important in influencing fire behaviour, but yet have not been considered.</p> <p>We test this by selecting three Triassic analogue species grown experimentally in different atmospheric compositions, and analyse variations in leaf chemistry, and leaf level flammability. These data were used to inform a fire behaviour model.</p> <p>We find that all three species tested showed a reduction in their volatile component, leading to lower flammability. Accounting for these variations in a model, our results suggest that leaf intrinsic flammability has a measurable impact on modelled fire behaviour.</p> <p>If scaled up to ecosystem level, periods of elevated CO<sub>2</sub> may therefore be capable of inducing both biochemical and morphological changes in fuel properties, and thus may be capable of influencing fire behaviour.</p>
Volatile organic compounds (VOIs) in seawater and sediment pore water collected in Funka Bay and Bering and Chukchi Seas
<p>The data of volatile organic compounds (VOIs) in seawater and sediment pore water collected in the Funka Bay, Hokkaido, Japan, and the Bering and Chukchi Seas. Funka Bay's samples were collected in 2018-2019. Bering and Chukchi Seas' samples were collected in July of 2017 and 2018. The article entitled "Marine sediment as a likely source of methyl and ethyl iodides in subpolar and polar seas" by Ooki et al. published by Communications Earth & Environment used these datasets. The datasets are also provided as supplementary data1-4 in the article. Details of datasets are described in the article. Please cite this article when you use these datasets.</p>
Effect of water availability on volatile-mediated communication between potato plants in response to insect herbivory
<p>Airborne plant communication is a widespread phenomenon in which volatile organic compounds (VOCs) from damaged plants boost herbivore resistance in neighbouring, undamaged plants. Although this form of plant signalling has been reported in more than 30 plant species, there is still a considerable knowledge gap on how abiotic factors (e.g., water availability) alter its outcomes.</p> <p>We performed a greenhouse experiment to test for communication between potato plants (<em>Solanum tuberosum</em>) in response to herbivory by the generalist insect <em>Spodoptera exigua</em> and whether communication was affected by water availability. We paired emitter and receiver potato plants, with half of the emitters damaged by S. exigua larvae and half serving as undamaged controls. Both emitter and receiver plants were subjected to one of two water availability treatments: high (i.e., well-watered) vs. low (i.e., reduced watering) availability, thus effectively teasing apart water availability effects on the emission and reception components of signalling. After four days of herbivore feeding, we collected emitter VOCs and receivers were subjected to feeding by <em>S. exigua</em> to test for effects of signalling on induced resistance.</p> <p>Herbivory by <em>S. exigua</em> led to increased VOCs emissions as well as changes in VOCs composition in emitter plants. Furthermore, emitters subjected to low water availability exhibited a weaker induction of VOCs in response to herbivory relative to well-watered emitters. Results from the feeding bioassay indicated that receivers exposed to VOCs from herbivore-induced emitters showed lower S. exigua damage (i.e. higher induced resistance) compared to receivers exposed to undamaged emitters. However, we did not observe a significant effect of water availability in either emitters or receivers on plant communication.</p> <p>Overall, our study contributes to the understanding of how the abiotic context affects plant communication by providing evidence of water availability effects on the induction of VOCs that may act as airborne signals between plants. The observed changes in induced VOCs had no visible consequences for plant communication. These findings thus suggest that the induction of key compounds mediating communication was not compromised by our experimental conditions.</p>
Insect Odorant Binding Protein Dataset of Binding Affinities against Volatile Organic Compounds
<p>This is an archival version of the initial iOBPdb dataset of insect odorant binding protein binding affinities against volatile organic compounds. It contains 215 functional studies containing 381 unique OBPs from 91 insect species.</p>
Data and code for theoretical analyses for the evolution of biogenic volatile organic compounds (BVOCs) emission strategy
<p>These are Python code for analysis and JSON data obtained by simulation with the lattice model.</p> <p>To visualize figures better, we have slightly modified the content of "LatticeModelVisualization.ipynb".</p>
Quantification of volatile organic compound emissions from unconventional oil and gas development
<p>Oil and gas (O&G) development in the U.S. has accelerated in the past two decades, aided by unconventional extraction techniques including hydraulic fracturing and horizontal drilling. Potential environmental and health impacts of volatile organic compounds (VOCs) originating from O&G activities in populated regions have raised concerns. In Broomfield, Colorado, six new O&G well pads were approved for development in 2017 and an air monitoring program was established in October 2018 to collect weekly and plume-triggered air samples. This study addresses the limited existing knowledge of activity-specific VOC emission rates from unconventional O&G development (UOGD), utilizing these observations and dispersion model simulations through emission inversion methods. Emissions are characterized from well drilling, hydraulic fracturing, coiled tubing/millout, flowback, and production operations.</p> <p>Substantial variations in average VOC emission rates, determined using weekly canister observations, are observed across different UOGD phases. Drilling and coiled tubing/millout operations exhibit the highest VOC emission rates, attributed to hydrocarbon release from shale formations and drilling mud. In contrast, hydraulic fracturing gives lower emission rates, consistent with injection of fluids into the well, minimizing the probability of subsurface hydrocarbon emissions. Diesel-powered engines are identified as the primary ethyne sources during hydraulic fracturing. Production was characterized by lower VOC emission rates than pre-production phases but remains an important emission category due to its long duration (decades). Internal variations of emission rates within each phase highlight the complexity of factors and activities influencing emission rates, including, for example, vertical vs. horizontal drilling and periodic maintenance activities. VOC emission rates associated with drilling mud volatilization and hydraulic fracturing suggest that previously published emission estimates (EPA (2022), and Hecobian et al. (2019)) underestimate VOC emission rates during these activities. Significantly lower emission rates during flowback compared to previous work (Hecobian et al., 2019) reveal how improved management practices, including tankless, closed-loop fluid handling systems have effectively reduced what used to be a dominant source of pre-production VOC emissions. Plume-triggered samples, capturing transient high-concentration plumes, reveal short-term VOC emission rates approximately ten times higher for drilling and flowback than determined from weekly samples. In the case of flowback, short-term emission pulses have been linked to periodic emptying of sand canisters used to trap fracking sand emerging from previously fracked wells.</p>
Low molecular weight reduced sulfur substances: a major component of non-volatile dissolved organic sulfur in the Pacific Ocean
<p>The low molecular weight (LMW) reduced sulfur substances (RSS) composition of dissolved organic matter (DOM) was examined along the GEOTRACES US-GP15 section in the Pacific Ocean. We demonstrate that LMW RSS constitutes a significant fraction of non-volatile dissolved organic sulfur (DOS). While thiols such as glutathione were below our detection limit (300 pM), RSS containing two carbon (C) sulfur (S) bonds were present at concentrations in the hundreds of nM range. RSS accumulation was observed in subtropical waters. The most likely source of these RSS is microbial alteration of sulfurized DOM with production of secondary thioamidated metabolites. RSS are initially produced by cyanobacteria to mitigate copper and oxidative stress induced by UV-B irradiance. A preferential remineralization of RSS over dissolved organic carbon (DOC) in the upper 350 meters suggests a partial lability of LMW DOS. Deeper, homogeneous concentrations and C:S ratio indicate increasing stability of this LMW DOS.</p>
The Full Results and Dataset of Research of Refactoring Volatility
<p>This database is available duplication of the submmitted paper.The details are described below to facilitate replication of the experiment:</p> <ul> <li>Refactoring dataset.zip is a refactoring dataset of 48 projects, stored in json format, including the specific data of 807651 refactoring instances. The shared data can be provided for other research to further expand based on this data.</li> <li>oddsRatioResults.csv is the complete result of RQ1, including odd ratios and p values for 90 refactoring types.</li> <li>Rq2-datacollecting.py is a Python script used in RQ2 to collect different metrics, including metrics for the churn/history/experience dimension.</li> <li>sampling_result.json is a sample data set used in RQ4 to analyze the cause of refactoring volatility.</li> <li>RQ4 - Reasons explaination(Pictures).zip is the specific examples for different reasons for refactoring volatility, including a screenshot of the refactoring code changes at commits.</li> </ul>
Replication files for "Distance(s) and the volatility of international trade(s) (2024)" by Arnaud Mehl, Giulia Sabbadini, Martin Schmitz, and Cedric Tille, European Economic Review 167
<p>Replication files for "Distance(s) and the volatility of international trade(s) (2024)" by Arnaud Mehl, Giulia Sabbadini, Martin Schmitz, and Cedric Tille, European Economic Review 167. Science direct : https://www.sciencedirect.com/science/article/pii/S0014292124000862?via%3Dihub</p> <p>Contains three folder, each with detailed steps: </p> <p>-Replication_country_level_results</p> <p>-Replication_product_level_results</p> <p>-Tables_figures</p>
volatile organic compounds that were measred at the Dead Sea - Israel (both terrestrial and coastal; Anthropogenic and biogenic)
<p>Multiple VOCs (biogenic and anthropogenic) were sampled by our research group at various terrestrial and coastal sites around the Dead Sea (Israel). Analysis was conducted by Prof. Donald Blake, and the data were included in a publication available at <a href="https://acp.copernicus.org/articles/19/7667/2019/" target="_new" rel="noreferrer">https://acp.copernicus.org/articles/19/7667/2019/</a>.</p>
Fig. 1 in Trapping Drosophila repleta (Diptera: Drosophilidae) using color and volatiles
Fig. 1. Spectrophotometer analysis of colors used in laboratory and field experiments.
Dataset on the characterization of the flavor of two red wine varieties using sensory descriptive analysis, volatile organic compounds quantitative analysis by GC-MS and odorant composition by GC-MS-O
<p>The dataset contains data that were collected on 2 sets of 8 French red wines from two grape varieties, Pinot Noir (PN) and Cabernet Franc (CF). It provides, for the 16 wines, (i) sensory descriptive data obtained with a trained panel, (ii) volatile organic compounds (VOC) quantification data obtained by Gas Chromatography–Mass Spectrometry (GC-MS) and (iii) odorant composition obtained by Gas Chromatography–Mass Spectrometry–Olfactometry (GC-MS-O).</p> <p> </p> <p>The dataset is a Microsoft Excel Worksheet containing 8 sheets.</p> <p>- Sheet 1: Information</p> <p>Gives information about the sheets contained in this .xlsx file</p> <p>- Sheet 2: Experimental_factors</p> <p>Each row represents a wine</p> <p>Each column corresponds to an experimental factors of the wines (Grape variety, Vintage and Protected Designation of Origin)</p> <p>- Sheet 3: List_sensory_descriptors</p> <p>Lists the 33 sensory descriptors used for the sensory descriptive analysis of the wines</p> <p>- Sheet 4: Sensory_descriptive_analysis</p> <p>Each row represents a wine</p> <p>Each column corresponds to a condition (2640 columns)</p> <p>Senso_(ortho or retro)_(Panelist1 to Panelist 16)_(1 to 33 Sensory descriptors)_(1 to 3 repetitions for ortho and 1 to 2 repetitions for retro)</p> <p>For the ortho (orthonasal) measurements, there is 16 panelists, 33 sensory descriptors and 3 repetitions = 1584 columns</p> <p>For the retro (retronasal) measurements, there is 16 panelists, 33 sensory descriptors and 2 repetitions = 1056 columns</p> <p>Each cell contains a sensory measurement for the corresponding condition in the corresponding wine</p> <p>- Sheet 5: List_VOC</p> <p>Lists the 45 VOC quantified in the wines with their corresponding CAS number</p> <p>VOC: Volatil Organic Compounds</p> <p>- Sheet 6: VOC_quantification</p> <p>Each row represents a wine</p> <p>Each column corresponds to a VOC (45 columns)</p> <p>Each cell contains the quantification of the corresponding VOC in the corresponding wine</p> <p>- Sheet 7: List_GC-MS-O</p> <p>Lists the 49 odor-active compounds identified with their corresponding CAS number and the 34 compounds identified by their apex indice</p> <p>- Sheet 8: GC-MS-O</p> <p>Each row represents a wine</p> <p>Each column corresponds to an odor-active compound identified by its CAS number or by its Apex indice if the compound was not identify (81 odor-active compounds) + the number of judges who smelled the compound and its description (by 8 judges) = 9 columns per odor-active compound for a total of 729 columns</p>
Technical note: Interferences of volatile organic compounds (VOC) on methane concentration measurements - Raw Data
<p>Technical note: Interferences of volatile organic compounds (VOC) on methane concentration measurements - Raw Data</p>
Geochemical evidence for high volatile fluxes from the mantle at the end of the Archean: matlab code
<p>This is the matlab code used to compute past fluxes of mantle-derived Xe to account for the isotopic evolution of atmospheric Xe. </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.
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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.