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505 results for “apple”
Illumina sequencing data of Agro-mediated gene-edited apple lines
<p>FastaQ pair-end Illumina sequencing data of the Dipm1/4, Hipm1, and Mlo19 genes from the different apple Agro-edited lines obtained in the project. GA = Gala; GD = Golden Delicious</p> <p>Lines included are:</p> <p>GA1, GA3, GA4, GA5, and GA WT</p> <p>GD1, 2, 6, 10, 11, 12, 15, 17, 18, 19, 20, 21, 23, 24, 26, 27, 29, 31, 33, 36, 37, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, and WT</p>
Evaluating 3D Human Motion Capture using Apple ARKit against the Vicon System: A Dataset
<p><strong>A journal paper which was published in Applied Sciences gives detailed information about the dataset.</strong></p> <p>Reimer, L.M.; Kapsecker, M.; Fukushima, T.; Jonas, S.M. Evaluating 3D Human Motion Capture on Mobile Devices. Appl. Sci. <em>(2022)</em></p> <p><a href="https://www.mdpi.com/2076-3417/12/10/4806">https://www.mdpi.com/2076-3417/12/10/4806</a></p> <p>Please cite the corresponding paper when using the dataset.</p> <p> </p> <p>A dataset containing anonymized exercise data for eight exercises from ten subject. The exercise data was recorded with two iPads 11" (2021 version, Apple Inc., Cupertino, CA, USA) and a Vicon system. The two iPads were positioned frontal and in a 30° angle to the left side of the subject. The Vicon system used 14 cameras and captured the motion using the Full-body Plug-in-gait model.</p> <p>The dataset contains 220 files, 22 per subject. The structure of the dataset contains 10 folders, one per subject. Each folder contains two subfolders: ARKit and Vicon. Each ARKit folder holds two CSV files. Each Vicon folder holds 16 files, two per exercise: a .csv file with the motion data and a .xcp file containing meta data about the recording, including the camera setup and start/stop timestamps.</p> <p>Du to export problems, the ARKit files for the Side View do not always contain all joint data. The upper body joints are only available for three out of the ten subjects for the Side View.</p>
Pollination deficits and contributions of pollinators in apple production: a global meta-analysis
<p>1. Apple is one of the most widely cultivated fruit crops worldwide, and apple yield benefits from pollination by insects. The global decline in wild pollinator populations raises concern about the adequacy of pollination services in apple production.</p> <p>2. Here, we present a global meta-analysis of pollination in apple. We assembled from the literature a dataset comprising results of 48 studies across five continents on fruit set and seed set in apple with insect pollination, artificial pollination and pollinator exclusion, and analysed the effects of explanatory factors such as variety and continent.</p> <p>3. Fruit set was on average 41% lower with open pollination than with artificial pollination, while seed set was 20% lower. These pollination deficits varied across continents and cultivars. Pollination deficits for fruit set were greatest in Asia (63%) followed by Europe (30%), whereas pollination deficits for seed set were greatest in Asia (47%) and South America (40%). Important differences in pollination deficit were also identified between cultivars but these differences were confounded with continent effects.</p> <p>4. Fruit set and seed set were 71% and 62% higher, respectively, when insects had open access to flowers than when they were artificially excluded, while results varied among cultivars.</p> <p>5. Synthesis and Applications. Globally, there are substantial contributions of pollinators to fruit set and seed set in apple, as well as considerable limitations in apple pollination services, particularly in Asia, Europe and South America. Several management strategies could be applied to reduce the pollination deficits in apple production: (1) conserving wild bees and enhancing their abundance and diversity, (2) using managed bees for pollination, (3) using varieties with low pollinator dependency, and/or (4) artificial pollination. These strategies should be tailored to the regional situation, considering the potential of landscapes for restoring wild pollinators, the acceptability of cultivated varieties for available pollinators, the acceptance in the market of self-compatible varieties, and the costs of management, such as artificial pollination, pollinator conservation, beekeeping and planting self-compatible varieties. Conservation of wild pollinators is preferred in regions with sufficient potential for wild pollinators as it contributes to biodiversity conservation and improves pollination in both crops and wild plants.</p>
Data and code for Bauer et al. (2018) Riv Res Appl
<p>Data and code for:</p> <p>Bauer M, Harzer R, Strobl K, Kollmann J (2018) <strong>Resilience of riparian vegetation after restoration measures on River Inn.</strong> – <em>River Research and Applications</em>, 34, 451–460. <a href="https://doi.org/10.1002/rra.3255">https://doi.org/10.1002/rra.3255</a></p> <p><a href="https://github.com/markus1bauer/2018_alluvial_forest_river_ammer/blob/main/README.md">GitHub README</a></p> <p> </p>
Figure 1 in Functional response of the predatory mite, Typhlodromus bagdasarjani (Acari: Phytoseiidae) to protonymphs of Eotetranychus frosti (Acari: Tetranychidae) on four apple cultivars
Figure 1 The functional responses curves of adult females of Typhlodromus bagdasarjani to different densities ofEotetranychus frosti protonymphs on four apple cultivars.
Astur Apple image Dataset
<p>Struture of file: 2022-v2-9classes-AsturApple-Balanced-SIZE224-train-dev-test.hdf5<br> -------------------------------------------------------------------------------------------<br> This file contains dataset of 6108 cider apple color images, 224x224 pixels to support the article "Transfer learning with convolutional neural networks<br> for classification of cider apple varieties" results.</p> <p>-The images belong to nine apple classes: 'BLANQUINA' 'CARRIO' 'FLORINA' 'FUENTES' 'PRIETA' 'RAXAO' 'REINETA ENCARNADA' 'REINETA PINTA' 'REINETA ROJA DEL CANADA'<br> -Full dataset is split in 4886 images for training, 611 for testing and 611 for validation.<br> -Class labels are codified as one-hot enconding binary labels. (e.g. [0 0 0 0 0 1 0] ---> Reineta Pinta)<br> -Training image set are store as tensor "trainX": (4168,224,224,3)<br> -Training class labels "trainY": (4886,7)<br> -Test image set tensor "testX": (611, 224,224,3)<br> -Test image binary class labels "testY": (611, 7)<br> -Validation image set tensor "devX": (611, 224,224,3)<br> -Validation binary class labels "devY": (611, 7)</p> <p>* file was created with h5py module in Python.</p> <p> </p>
Data for "High-accuracy determination of Paul-trap stability parameters for electric-quadrupole-shift prediction", J. Appl. Phys. 132, 124401 (2022)
<p>Data required to reproduce the key results in: "High-accuracy determination of Paul-trap stability parameters for electric-quadrupole-shift prediction", J. Appl. Phys. <strong>132</strong>, 124401 (2022). <a href="https://doi.org/10.1063/5.0106633">https://doi.org/10.1063/5.0106633</a></p> <ul> <li>The file "sec_freq.dat" contains measured secular frequencies, the rf frequency, the applied bias voltages, and the MJD of the measurement: <ul> <li>Figures 4-5 use rows 31-33 of this data.</li> <li>Figure 6 uses all data corresponding to -1.1e-3 < <em>a</em><sub>x</sub> < -0.6e-3.</li> <li>Figure 7(a) uses all the data.</li> </ul> </li> <li>The file "data2021-12-21_MJD.txt" contains the secular frequency data used to derive Eq. (16) and plot Figure 8.</li> <li>The file "RF_monitor_rectifier_1d.txt" contains the rectified monitor voltage used in Figure 8.</li> <li>The file "Temperature_108_1d.txt" contains the helical-resonator temperature used in Figure 8.</li> <li>The file "Fig9_EQS.dat" contains the measured electric quadrupole shift (EQS) used for Figure 9.</li> <li>The file "interleavedEQS.dat" contains the data from the interleaved EQS measurement used to determine a lower value of 1070 for the cancellation factor.</li> </ul>
Extracts from Meador et al., 2022, Appl Cognit Psychol
Open the record for dataset details and reuse information.
Planteome/CO_370-apple-traits: Apple Trait Ontology v1.0
<p>This is the first release of the Apple Trait Ontology that is published online the <a href="https://cropontology.org/">Crop Ontology Web site</a></p>
Dataset: Apple Inc. (AAPL) 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: Apple Inc. (AAPL) 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.
Figure 1 in Effect of a short-cycle apple tree cultivar on oriental fruit moth (Lepidoptera: Tortricidae) development and larval behavior
Figure 1. Average number of Grapholita molesta males captured monthly by pheromone-bait traps in 'Eva' and 'Gala' apple orchards during seven years in Porto Amazonas, Paraná, Brazil.
Figure 2 in Determination of the ursolic and oleanolic acids content with the antioxidant capacity in apple peel extract of various cultivars
Figure 2. HPLC chromatogram of ursolic acid and oleanolic acid: Standards (500 µg/ml) (A), Apple peel methanolic extract for Red Delicious (B), Granny Smith (C) and, Royal Gala (D) cultivars. UA: ursolic acid; OA: oleanolic acid.
Figure 4 in Determination of the ursolic and oleanolic acids content with the antioxidant capacity in apple peel extract of various cultivars
Figure 4. Correlation analysis of the concentration (µg/ml) of ursolic acid (UA) and oleanolic acid (OA) in Red Delicious (A, B); Granny Smith (C, D); and Royal Gala (E, F) with the antioxidant capacity (%) of the various cultivars. A value of r between 0 –1 indicates a strong positive correlation.
Figure 3 in Determination of the ursolic and oleanolic acids content with the antioxidant capacity in apple peel extract of various cultivars
Figure 3. Antioxidant activity of the apple peel extracts from various cultivars. *Significant difference p <0.001.
Figure 1 in Effects of Indole-3-Butyric Acid (IBA) and rooting media on rooting and survival of air layered wax apple (Syzygium samarangense) CV Jambu Madu
Figure 1. Effects of different rooting media and various concentrations of IBA on the rooting of wax apple air layers. M C: Sphagnum 1 0 moss (wet) + IBA 0 mg L-1, M C: Vermicompost + IBA 0 mg L-1, M C: Garden soil + IBA 0 mg L-1, M C: Sphagnum moss (wet) + 2 0 3 0 1 1 IBA 1000 mg L-1, M C: Vermicompost + IBA 1000 mg L-1, M C: Garden soil + IBA 1000 mg L-1, M C: Sphagnum moss (wet) + IBA 2 1 3 1 1 2 1500 mg L-1, M C: Vermicompost + IBA 1500 mg L-1, M C: Garden soil + IBA 1500 mg L-1, M C: Sphagnum moss (wet) + IBA 2000 mg 2 2 3 2 1 3 L-1, M C : Vermicompost + IBA 2000 mg L-1 and M C : Garden soil + IBA 2000 mg L-1.
Figure 3 in Effects of Indole-3-Butyric Acid (IBA) and rooting media on rooting and survival of air layered wax apple (Syzygium samarangense) CV Jambu Madu
Figure 3. Survival rate of air layers (%) of wax apple as affected by different concentrations of IBA and growing media after detaching from mother plants. M C: Sphagnum moss (wet) + IBA 1000 mg L-1, M C: Vermicompost + IBA 1000 mg L-1, M C: Garden soil + IBA 1 1 2 1 3 1 1000 mg L-1, M C: Sphagnum moss (wet) + IBA 1500 mg L-1, M C: Vermicompost + IBA 1500 mg L-1, M C: Garden soil + IBA 1500 mg L-1, 1 2 2 2 3 2 M C : Sphagnum moss (wet) + IBA 2000 mg L-1, M C : Vermicompost + IBA 2000 mg L-1 and M C : Garden soil + IBA 2000 mg L-1.
Figure 2 in Effects of Indole-3-Butyric Acid (IBA) and rooting media on rooting and survival of air layered wax apple (Syzygium samarangense) CV Jambu Madu
Figure 2. Effects of IBA hormones and different rooting media on the survivability of rate of wax apple air layered. M 1 C 0: Sphagnum moss (wet) + IBA 0 mg L-1, M C: Vermicompost + IBA 0 mg L-1, M C: Garden soil + IBA 0 mg L-1, M C: Sphagnum moss (wet) + IBA 2 0 3 0 1 1 1000 mg L-1, M C: Vermicompost + IBA 1000 mg L-1, M C: Garden soil + IBA 1000 mg L-1, M C: Sphagnum moss (wet) + IBA 1500 mg L-1, 2 1 3 1 1 2 M C: Vermicompost + IBA 1500 mg L-1, M C: Garden soil + IBA 1500 mg L-1, M C: Sphagnum moss (wet) + IBA 2000 mg L-1, M C: 2 2 3 2 1 3 2 3 Vermicompost + IBA 2000 mg L-1 and M C: Garden soil + IBA 2000 mg L-1. Bars represent means (n = 7) ± standard error (S.E.). a, b, and 3 3 c indicate significant differences within each growth period (p <0.05).
Fig. 1 in Influence of sun and shade conditions on Gratiana boliviana (Coleoptera: Chrysomelidae) abundance and feeding activity on tropical soda apple (Solanaceae) under field conditions
Fig. 1. Mean feeding damage score (± SE) for all 3 sampling dates caused by Gratiana boliviana beetles to tropical soda apple plants under 3 light conditions: unshaded, partially shaded, and shaded. Means with the same letter are not significantly different (P <0.05: Kruskal–Wallis, Dunn's test).
Рис. 2. Варианты преΑсказанной Αоменной структуры патогенраспознающих моΛекуΛ гемоцитов моΛΛюсков Planorbarius corneus. a — фибриногенпоΑобные беΛки, b — гаΛектины, c — F-Λектины. УсΛовные обозначения и сокращения, зΑесь и ΑаΛее: горизонтаΛьные красные поΛоски — сигнаΛьный пептиΑ, горизонтаΛьные розовые — обΛасть низкой сΛожности, вертикаΛьные синие поΛоски — трансмембранная обΛасть, FBG — фибриногеновый Αомен, FTP — Αомен фукоΛектина, EGF — Αомен эпиΑермаΛьного фактора роста, EGF_CA — каΛьцийсвязывающий EGF-поΑобный Αомен, PAN_AP — APPLE-поΑобный Αомен, SCAN — обΛасть, богатая Λейцином, GLECT — гаΛактозосвязывающий Λектин, CLECT — Λектин C-типа, Gal-bind — гаΛактозиΑ–связывающий Λектин, ML — MD-2- поΑробный Αомен распознавания ΛипиΑов Fig. 2. Variants of the predicted domain structure of pattern recognition molecules from hemocytes of Planorbarius corneus molluscs. a — fibrinogen-related proteins, b — galectins, c — F-lectins. Symbols and abbreviations (here and further): horizontal red stripes — signal peptide, horizontal pink stripes — a low complexity region, vertical blue stripes — transmembrane region, FBG — fibrinogen-related domain, FTP — fucolectin domain, EGF — epidermal growth factor-like domain, EGF_CA — calcium-binding EGF-like domain, PAN_AP — APPLE-like domain, SCAN — leucine rich region, Apple — APPLE domain, GLECT — galactose-binding lectin, CLECT — C-type lectin, Gal-bind — galactoside-binding lectin, ML — MD-2-related lipid-recognition domain in Pathogen recognition molecules from hemocytes of Planorbarius corneus molluscs (Planorbidae, Pulmonata)
Рис. 2. Варианты преΑсказанной Αоменной структуры патогенраспознающих моΛекуΛ гемоцитов моΛΛюсков Planorbarius corneus. a — фибриногенпоΑобные беΛки, b — гаΛектины, c — F-Λектины. УсΛовные обозначения и сокращения, зΑесь и ΑаΛее: горизонтаΛьные красные поΛоски — сигнаΛьный пептиΑ, горизонтаΛьные розовые — обΛасть низкой сΛожности, вертикаΛьные синие поΛоски — трансмембранная обΛасть, FBG — фибриногеновый Αомен, FTP — Αомен фукоΛектина, EGF — Αомен эпиΑермаΛьного фактора роста, EGF_CA — каΛьцийсвязывающий EGF-поΑобный Αомен, PAN_AP — APPLE-поΑобный Αомен, SCAN — обΛасть, богатая Λейцином, GLECT — гаΛактозосвязывающий Λектин, CLECT — Λектин C-типа, Gal-bind — гаΛактозиΑ–связывающий Λектин, ML — MD-2- поΑробный Αомен распознавания ΛипиΑов Fig. 2. Variants of the predicted domain structure of pattern recognition molecules from hemocytes of Planorbarius corneus molluscs. a — fibrinogen-related proteins, b — galectins, c — F-lectins. Symbols and abbreviations (here and further): horizontal red stripes — signal peptide, horizontal pink stripes — a low complexity region, vertical blue stripes — transmembrane region, FBG — fibrinogen-related domain, FTP — fucolectin domain, EGF — epidermal growth factor-like domain, EGF_CA — calcium-binding EGF-like domain, PAN_AP — APPLE-like domain, SCAN — leucine rich region, Apple — APPLE domain, GLECT — galactose-binding lectin, CLECT — C-type lectin, Gal-bind — galactoside-binding lectin, ML — MD-2-related lipid-recognition domain
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.