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6,452 results for “Application”
Multiscale modeling of lubrication between rough surfaces: Application to gas lubrication - Dataset
<p>Data set used for the paper entitled "Multiscale modeling of lubrication between rough surfaces: Application to gas lubrication"</p> <p>The associated paper is archived on an open access aichive: https://hal.archives-ouvertes.fr/hal-03402682</p>
Wind profile in the wave boundary layer and its application in a coupled atmosphere-wave model
<p>The simulation data for the study</p>
Photophysics of perylene diimide dianions and their application in photoredox catalysis
<p>Raw data from optical spectroscopic and electrochemical experiments in an Igor Pro file, version 6.3.7.2</p>
Figure 3 from: Linh NN, Hang PLB, Hue HTT, Ha NH, Hanh HH, Ton ND, Hien LTT (2022) Species discrimination of novel chloroplast DNA barcodes and their application for identification of Panax (Aralioideae, Araliaceae). PhytoKeys 188: 1-18. https://doi.org/10.3897/phytokeys.188.75937
Figure 3 Successful identification rates among analyzed barcodes by Best Match and Best Close Match function.
Figure 2 from: Linh NN, Hang PLB, Hue HTT, Ha NH, Hanh HH, Ton ND, Hien LTT (2022) Species discrimination of novel chloroplast DNA barcodes and their application for identification of Panax (Aralioideae, Araliaceae). PhytoKeys 188: 1-18. https://doi.org/10.3897/phytokeys.188.75937
Figure 2 Percent relative abundance in distribution of intra/interspecific K2P pairwise distances estimated for markers.
Figure 5 from: Linh NN, Hang PLB, Hue HTT, Ha NH, Hanh HH, Ton ND, Hien LTT (2022) Species discrimination of novel chloroplast DNA barcodes and their application for identification of Panax (Aralioideae, Araliaceae). PhytoKeys 188: 1-18. https://doi.org/10.3897/phytokeys.188.75937
Figure 5 Percentage of variable sites, mean pairwise distances, and correct classification percentages of all markers and combinations
Figure 4 from: Linh NN, Hang PLB, Hue HTT, Ha NH, Hanh HH, Ton ND, Hien LTT (2022) Species discrimination of novel chloroplast DNA barcodes and their application for identification of Panax (Aralioideae, Araliaceae). PhytoKeys 188: 1-18. https://doi.org/10.3897/phytokeys.188.75937
Figure 4 Results of mPTP species delimitation analysis for several markers based on ML trees A Species delimitation for marker trnQ-rps16B Species delimitation for the combination of markers 1+3+4. Bootstrap values are displayed on the branches. The red branches represent supported species delimitations. Sequences highlighted in orange originate from this study.
Figure 1 from: Linh NN, Hang PLB, Hue HTT, Ha NH, Hanh HH, Ton ND, Hien LTT (2022) Species discrimination of novel chloroplast DNA barcodes and their application for identification of Panax (Aralioideae, Araliaceae). PhytoKeys 188: 1-18. https://doi.org/10.3897/phytokeys.188.75937
Figure 1 Distribution of Panax in Vietnam and sample locations. P. vietnamensis (green) collected in Quang Nam and Kon Tum Provinces. P. vietnamensis var. fuscidiscus (brown) collected in Lai Chau Province. Panax sp. Puxailaileng (pink) collected in Nghe An Province. P. bipinnatifidus (blue) and P. stipuleanatus (yellow) collected in Lao Cai Province. The natural distribution of P. vietnamensis, P. vietnamensis var. fuscidiscus, and Panax sp. are marked as green, brown, and pink, respectively. The wild habitat for P. bipinnatifidus and P. stipuleanatus is shown in yellow, and the purple area represents the distribution region of P. vietnamensis var. langbiangensis (not included in this study).
A wavelength and polarization selective photon sieve for holographic applications
<p>Dataset of the publication "A wavelength and polarization selective photon sieve for holographic applications" Nanophotonics 10 (18), 4543-4550 (2021) (10.1515/nanoph-2021-0440).</p>
Application of health belief model for the assessment of COVID-19 preventive behavior and its determinants among students: A structural equation modeling analysis
<p><strong>Background:</strong> COVID-19 is a new pandemic that poses a threat to people globally. In Ethiopia, where classrooms are limited, students are at higher risk for COVID-19 unless they take consistent preventative actions. However, there is a lack of evidence in the study area regarding student compliance with COVID-19 preventive behavior (CPB) and its predictors.</p> <p><strong>Objective:</strong> This study aimed to assess CPB and its predictors among students based on the perspective of the Health Belief Model (HBM).</p> <p><strong>Method and materials:</strong> A school-based cross-sectional survey was conducted from November to December 2020 to evaluate the determinants of CPB among high school students using a self-administered structured questionnaire. 370 participants were selected using stratified simple random sampling. Descriptive statistics were used to summarize data, and partial least squares structural equation modeling (PLS-SEM) analyses to evaluate the measurement and structural models proposed by the HBM and to identify associations between HBM variables. A T-value of > 1.96 with 95% CI and a P-value of < 0.05 were used to declare the statistical significance of path coefficients.</p> <p><strong> Result:</strong> A total of 370 students participated with a response rate of 92%. The median (interquartile range) age of the participants (51.9% females) was 18 (2) years. Only 97 (26.2%), 121 (32.7%), and 108 (29.2%) of the students had good practice in keeping physical distance, frequent hand washing, and facemask use respectively. The HBM explained 43% of the variance in CPB. Perceived barrier (β= - 0.15, p < 0.001) and self-efficacy (β= 0.51, p <0.001) were significant predictors of student compliance to CPB. Moreover, the measurement model demonstrated that the instrument had acceptable reliability and validity.</p> <p><strong>Conclusion and recommendations:</strong> COVID-19 prevention practice is quite low among students. HBM demonstrated adequate predictive utility in predicting CPBs among students, where perceived barriers and self-efficacy emerged as significant predictors of CPBs. According to the findings of this study, theory-based behavioral change interventions are urgently required for students to improve their prevention practice. Furthermore, these interventions will be effective if they are designed to remove barriers to CPBs and improve students' self-efficacy in taking preventive measures.</p>
Application of ATLD-MCR to gas chromatography-mass spectrometric data for the quantification of PAHs in aerosols
<p>In the work, for the first time, alternating trilinear decomposition-assisted multivariate curve resolution (ATLD-MCR) was applied to analyse complex gas chromatography–mass spectrometric (GC-MS) data with severe baseline drifts, serious co-elution peaks and slight retention time shifts for the simultaneous identification and quantification of polycyclic aromatic hydrocarbons (PAHs) in aerosols. It was also compared with the classic multivariate curve resolution-alternating least-squares (MCR-ALS) and the GC-MS-based external standard method. In validation samples, average recoveries of five PAHs were within the range from (96.2 ± 6.8)% to (106.5 ± 4.1)% for ATLD-MCR, near to the results of MCR-ALS ((98.0 ± 1.5)% to (106.7 ± 4.3)%). In aerosol samples, the concentrations of pyrene provided by ATLD-MCR were not significantly different from those of MCR-ALS. The other four PAHs including chrysene, benzo[a]anthracene, fluoranthene and benzo[b]fluoranthene were not detected by ATLD-MCR and the GC-MS-based external standard method. The results of figures of merit further demonstrated that ATLD-MCR achieved high sensitivities (8.9 × 104 to 1.7 × 106 mAU ml µg−1) and low limits of detection (0.003 to 0.087 µg ml−1), which were better than or similar to MCR-ALS, presenting a great choice to deal with complex GC-MS data for the simultaneous determination of targeted PAHs in aerosols.</p>
ATITPhysics 2022W - Witten Index and Applications
<p>These lecture series are given in ATITPhysics 2022 Winter School.</p>
Datasets for the integration of MT data with magnetic inversion: proof-of-concept using synthetic data and field application
<p>This dataset is a companion dataset to the manuscript "<strong>Utilisation of probabilistic MT inversions to constrain magnetic data inversion: proof-of-concept and field application</strong>", by Jérémie Giraud, Hoël Seillé, Mark D. Lindsay, Gerhard Visser, Vitaliy Ogarko, and Mark W. Jessel. <br><br>It contains models and data shown in the paper.<br><br>The document was submitted for publication in Solid Earth: <br>https://se.copernicus.org/preprints/se-2021-124/se-2021-124-manuscript-version2.pdf<br><br>The folder organisation is as follows, where <strong>bold</strong> refers to folders and subfolders, and text in <i>italic</i> corresponds to a succinct description of the contents.<br><br>|-- <strong>Dataset_synth</strong> > <i>synthetic dataset and results</i><br>| |-- <strong>Mag </strong>> <i>magnetic data and models: inversion and results </i><br>| | |-- <strong>domains </strong>> <i>contains the files used to define domains for inversion</i><br>| | |-- <strong>inversion results </strong>> <i> contains subfolders with inversion results for different cases </i><br>| | | |--<strong> case a </strong><br>| | | |--<strong> case b</strong><br>| | | |--<strong> case c</strong><br>| | | |-- <strong>case d</strong><br>| | | |-- <strong>case e</strong><br>| | | |-- <strong>case f </strong><br>| | |-- <strong>membership values</strong> > <i>contain files with membership values for the cases (a)-(f)</i><br>| | |-- <strong>responses </strong>> <i>simulated data with and without noise</i><br>| | |-- <strong>true model </strong>> <i>true model used for simulation</i><br>| |-- <strong>MT </strong>> <i>MT probabilities, sites information and models</i><br>| | |-- <strong>probabilities </strong>> <i>MT-derived probabilities</i><br>| | |-- <strong>responses </strong>> <i>simulated MT data</i><br>| | | |-- <strong>edi_noise_5p </strong>> <i> 5% noise-contaminated data (*.edi files)</i><br>| | | |--<strong> </strong>MansfieldMT_fwd.dat > <i> uncontaminated (ModEM format *.dat file)</i><br>| | |-- <strong>model </strong>> <i>model in ModEM format (*.mod) and WinGLink format (.out) formats</i><br>| | |-- coordinates.txt ><i> location of MT sites</i><br>| |-- <strong>Rock units </strong>> <i>contains the file with indices of the rock unit model, in 3D, of the modified Mansfield model. The indices are stored as a column vector. </i><br><br>|-- <strong>Dataset_field</strong> > <i>field dataset</i><br>| |-- <strong>Mag </strong>> <i>magnetic data and models: inversion and results</i><br>| | |-- <strong>admm constraints </strong>> <i> file with bound constraints used in cases 3, 4, and adjusted case 4.</i><br>| | |-- <strong>data </strong>> <i> magnetic data for inversion, x, y, z, data column format.</i><br>| | |-- <strong>inverted models </strong>> <i> folders containing inversion results for the different cases tested</i><br>| | | |-- <strong>case 1</strong> <br>| | | |-- <strong>case 2</strong><br>| | | |-- <strong>case 3</strong><br>| | | |-- <strong>case 4</strong><br>| | | |-- <strong>case 4 adjusted</strong><br>| |-- <strong>MT </strong>> <i>MT probabilities and sites information</i><br>| | |-- <strong>probabilities </strong>> <i>MT probabilities of interface and rock units (*.txt files)</i><br>| | |-- coord_L26_sites > <i>File containing the location of sites along ligne L26</i></p>
Supplementary material 3 from: Zulian G, Marando F, Mentaschi L, Alzetta C, Wilk B, Maes J (2022) Green balance in urban areas as an indicator for policy support: a multi-level application. One Ecosystem 7: e72685. https://doi.org/10.3897/oneeco.7.e72685
Setting the context at local level
Supplementary material 1 from: Zulian G, Marando F, Mentaschi L, Alzetta C, Wilk B, Maes J (2022) Green balance in urban areas as an indicator for policy support: a multi-level application. One Ecosystem 7: e72685. https://doi.org/10.3897/oneeco.7.e72685
Tutorial
Supplementary material 4 from: Zulian G, Marando F, Mentaschi L, Alzetta C, Wilk B, Maes J (2022) Green balance in urban areas as an indicator for policy support: a multi-level application. One Ecosystem 7: e72685. https://doi.org/10.3897/oneeco.7.e72685
Greenness and changes in vegetation cover in not densely built areas
Supplementary material 2 from: Zulian G, Marando F, Mentaschi L, Alzetta C, Wilk B, Maes J (2022) Green balance in urban areas as an indicator for policy support: a multi-level application. One Ecosystem 7: e72685. https://doi.org/10.3897/oneeco.7.e72685
Setting the context at European Level
One-Step Grown Carbonaceous Germanium Nanowires and Their Application as Highly Efficient Lithium-Ion Battery Anodes
<p>Developing a simple, cheap, and scalable synthetic method for the fabrication of functional nanomaterials is crucial. Carbon-based nanowire nanocomposites could play a key role in integrating group IV semiconducting nanomaterials as anodes into Li-ion batteries. Here, we report a very simple, one-pot solvothermal-like growth of carbonaceous germanium (C-Ge) nanowires in a supercritical solvent. C-Ge nanowires are grown just by heating (380–490 °C) a commercially sourced Ge precursor, diphenylgermane (DPG), in supercritical toluene, without any external catalysts or surfactants. The self-seeded nanowires are highly crystalline and very thin, with an average diameter between 11 and 19 nm. The amorphous carbonaceous layer coating on Ge nanowires is formed from the polymerization and condensation of light carbon compounds generated from the decomposition of DPG during the growth process. These carbonaceous Ge nanowires demonstrate impressive electrochemical performance as an anode material for Li-ion batteries with high specific charge values (>1200 mAh g<sup>–1</sup> after 500 cycles), greater than most of the previously reported for other “binder-free” Ge nanowire anode materials, and exceptionally stable capacity retention. The high specific charge values and impressively stable capacity are due to the unique morphology and composition of the nanowires.</p>
Fig. 2 in Application Of Dna Barcoding In Taxonomy And Phylogeny: An Individual Case Of Coi Partial Gene Sequencing From Seven Animal Species
Fig. 2. Phylogenetic position of E. roumanicus, Bayesian inference phylogenetic tree. Sequences obtained by us are written in bold.
Application of sulfur and nitrogen doped carbon quantum dots as sensitive fluorescent nanosensors for the determination of saxagliptin and gliclazide
<p>In this study, highly fluorescent sulfur and nitrogen doped carbon quantum dots (S,N-CQDs) were used as fluorescent nanosensors for direct spectrofluorimetric estimation of each of gliclazide and saxagliptin without any pre-derivatization steps for the first time. S,N-CQDs were synthesized employing a simple hydrothermal technique using citric acid and thiosemicarbazide. The produced S,N-CQDs were characterized using different techniques including fluorescence emission spectroscopy, UV spectrophotometry, high resolution transmission electron microscopy, and FT-IR spectroscopy. Following excitation at 360 nm, S,N-CQDs exhibited a strong emission peak at 430 nm. The native fluorescence of S,N-CQDs was quantitatively enhanced by addition of increased concentrations of the studied drugs. The fluorescence enhancement of S,N-CQDs and the concentrations of the studied drugs revealed a wide linear relationship in the range of 30.0-500.0 μM and 75.0-600.0 µM with limits of detection of 5.0 μM and 10.15 µM for gliclazide and saxagliptin, respectively. The proposed method was efficiently utilized for determination of cited drugs in their commercial tablets with % recoveries ranging from 98.6 to 101.2% and low % RSD values (less than 2%). The mechanism of interaction between S,N-CQDs and the two drugs was studied. Validation of the proposed method was carried out in accordance with ICH guidelines.</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.