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1,294 results for “reactions”
Harnessing photoenzymatic reactions for unnatural biosynthesis in microorganisms
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Monitoring the evolution of relative product populations at early times during a photochemical reaction
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Normative behavioral data from the novel One Trail Trace escape reaction task (OTTER)
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Raw data accompanying: Ground reaction forces in monitor lizards (Varanidae) and the scaling of locomotion in sprawling tetrapods
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A model of spatio-temporal regulation within biomaterials using DNA reaction–diffusion waveguides
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A sensitive method for atmospheric sulfur dioxide determination by reaction cell inductively coupled plasma mass spectrometer
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Hierarchy of fear: experimentally testing ungulate reactions to lion, African wild dog and cheetah
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Data and code from: The evolution of developmental thresholds and reaction norms for age and size at maturity
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Data from: Size-resolved chemical composition of sub-20 nm particles from methanesulfonic acid reactions with methylamine and ammonia
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Data file for paper:Zalitis, Christopher; Kucernak, Anthony; Lin, Xiaoqian; Sharman, Jonathan, "Electrochemical Measurement of Intrinsic Oxygen Reduction Reaction Activity at High Current Densities as a Function of Particle Size for Pt<sub>4-x</sub>Co<sub>x</sub> /C (x=0,1,3) Catalysts", ACS Catalysis, 2020 - https://doi.org/10.1021/acscatal.9b04750
<p>The data in this spreadsheet was used to produce the figures in the paper </p> <p>Authors: Zalitis, Christopher; Kucernak, Anthony; Lin, Xiaoqian; Sharman, Jonathan</p> <p>Title: Electrochemical Measurement of Intrinsic Oxygen Reduction Reaction Activity at High Current Densities as a Function of Particle Size for Pt<sub>4-x</sub>Co<sub>x</sub> /C (x=0,1,3) Catalysts</p> <p>Journal: ACS Catalysis</p> <p>Year: 2020</p>
BIRAFFE: Bio-Reactions and Faces for Emotion-based Personalization
<p>We present <strong>BIRAFFE</strong>, a dataset consisting of <em><strong>electrocardiogram (ECG)</strong></em>, <em><strong>galvanic skin reaction (GSR)</strong></em> and changes in <em><strong>facial expression</strong></em> signals recorded during affect elicitation by means of <em><strong>audio-visual stimuli</strong></em> (from IADS and IAPS databases) and our two proof-of-concept <em><strong>affective games</strong></em> ("Affective SpaceShooter 2" and "Fred Me Out 2"). All the signals were captured using portable and low-cost equipment: BITalino (r)evolution kit for ECG and GSR, and Creative Live! web camera for face photos (further analyzed by MS Face API). </p> <p>Besides the signals, the dataset consists also of <em><strong>subjects' self-assessment</strong></em> of their affective state after each stimuli (with the use of two widgets: the first one with <em><strong>5 emoticons</strong></em> and the second with <em><strong>valence and arousal</strong></em> dimensions) and <em><strong>"Big Five" personality traits</strong></em> assessment (using NEO-FFI inventory).</p> <p>For detailed description see <em>BIRAFFE-AfCAI2019-paper.pdf</em>.<br> For preview of the files before downloading the whole dataset see <em>sample-SUB1107-[...]</em> files.</p> <p>All documents and papers that report on research that uses the BIRAFFE dataset should acknowledge this by <strong>citing the paper</strong>:<br> Kutt, K., Drążyk, D., Jemioło, P., Bobek, S., Giżycka, B., Rodriguez-Fernandez, V., & Nalepa, G. J. (2020). "BIRAFFE: Bio-Reactions and Faces for Emotion-based Personalization". In G. J. Nalepa, J. M. Ferrandez, J. Palma, & V. Julian (Eds.), Proceedings of the 3rd Workshop on Affective Computing and Context Awareness in Ambient Intelligence (AfCAI 2019) (CEUR-WS Vol. 2609). http://ceur-ws.org/Vol-2609/</p> <p>Our research related to the BIRAFFE dataset is summarized in:<br> Kutt, K., Drążyk, D., Bobek, S., & Nalepa, G. J. (2021). "Personality-Based Affective Adaptation Methods for Intelligent Systems". Sensors, 21(1), 163. https://doi.org/10.3390/s21010163</p>
Data for: Synthesis and assessment of schwertmannite/few-layer graphene composite for the degradation of sulfamethazine in heterogeneous Fenton-like reaction
<p> Schwertmannite, an iron oxyhydrosulfate mineral, can catalyze Fenton-like reaction to degrade organic contaminants, but the reduction of Fe(III) to Fe(II) on the surface of schwertmannite is a limiting step for the Fenton-like process. In the present study, the schwertmannite/few-layer graphene composite (sch-FLG) was synthesized to promote the catalytic activity of schwertmannite in Fenton-like reaction. It was found that schwertmannite can be successfully carried by FLG in sch-FLG composite, mainly via the chemical bond of Fe-O-C on the surface of sch-FLG. The sch-FLG exhibited a much higher catalytic activity than schwertmannite or FLG for the degradation of SMT in the heterogeneous Fenton-like reaction, which resulted from that the few-layer graphene can pass electrons efficiently. The degradation efficiency of SMT was around 100% under the reaction conditions of H<sub>2</sub>O<sub>2</sub> 200-500 mg L<sup>-1</sup>, sch-FLG dosage 1-2 g L<sup>-1</sup>, temperature 28-38 °C, and initial solution pH 1-9. During the repeated uses of sch-FLG in Fenton-like reaction, it maintained a certain catalytic activity for the degradation of SMT and the mineral structure was not changed. In addition, SMT may be finally mineralized in Fenton-like reaction catalyzed by sch-FLG, and the possible degradation pathways were proposed. Therefore, the sch-FLG is an excellent catalyst for SMT degradation in heterogeneous Fenton-like reaction.</p>
Data from: Testing the thermal limits: Non-linear reaction norms drive disparate thermal acclimation responses in Drosophila melanogaster
Critical thermal limits are important ecological parameters for studying thermal biology and for modelling species' distributions under current and changing climatic conditions (including predicting the risk of extinction for species from future warming). However, estimates of the critical thermal limits are biased by the choice of assay and assay conditions, which differ among studies. Furthermore, estimates of the potential for phenotypic plasticity (thermal acclimation) to buffer against future warming are usually based on single assay conditions and (usually linear) extrapolation from a few acclimation temperatures. We produced high resolution estimates of adult acclimation capacity for upper tolerance limits at different assay conditions (ramping rates and knock-down temperatures) using CTmax (dynamic) and knock-down (static) thermal assays in the model species Drosophila melanogaster. We found the reaction norms to be highly dependent on assay conditions. We confirmed that progressively lower ramping rates or higher knock-down temperatures led to overall lower tolerance estimates. More surprisingly, extended assays (lower ramping rates or lower knock-down temperatures) also led to increasingly non-linear reaction norms for upper thermal tolerance across adult acclimation temperatures. Our results suggest that the magnitude (capacity) and direction (beneficial or detrimental) of acclimation responses are highly sensitive to assay conditions. The results offer a framework for comparison of acclimation responses between different assay conditions and a potential for explaining disparate acclimation capacity theories. We advocate cautious interpretation of acclimation capacities and careful consideration of assay conditions, which should represent realistic environmental conditions based on species' ecological niches.
Raw Data to "Can Small Polyaromatics Describe Their Larger Counterparts for Local Reactions? A Computational Study on the H-Abstraction Reaction by an H-Atom from Polyaromatics"
<p>This data includes the Turbomole input files (without molecular orbitals) and output files (under <strong> DFT_and_CC_*tar</strong>) as well as the output of the xTB calculations (under <strong>xtb*tar</strong>) for different reactive sites of the polyaromatics (PAHs) studied in the related publication, for the reaction:<br> C<sub>X</sub>H<sub>Y</sub> + H -> C<sub>X</sub>H<sub>Y-1</sub> + H<sub>2</sub><br> <br> <strong>File structure:</strong></p> <ul> <li>The xtb*tar contains the xTB (xTB version 6.3.1) optimized structures for the parameterizations <strong>GFN0</strong>, <strong>GFN1</strong> and <strong>GFN2</strong>. The parameter set is indicated by the folder name "<strong>BACK_XTB_NATIVE_GFN0</strong>", "<strong>BACK_XTB_NATIVE_GFN1</strong>" and "<strong>BACK_XTB_NATIVE_GFN2</strong>"<br> </li> <li>The DFT calculations are carried out at the <strong>TPSSh-D3/TZVP </strong>level and they are directly under the subdirectories of dft*tar folders (C*H*) and are used to calculate the data under <strong>Figure 3</strong> and <strong>4</strong> of the related publication, as well as to calculate partition functions which are listed under <strong>freeh.out</strong>,<strong> </strong>the output of the freeh program of Turbomole.<br> </li> <li>The coupled cluster calculations are always located under the subdirectories of the DFT calculations.<br> </li> <li>The subdirectories <strong>PNO-CC.tz</strong> are <strong>PNO-CCSD/cc-pVTZ</strong> calculations and the output files are named as 'pnoccsd.out.tpno.7' or 'pnoccsd.out.tpno.8', where 7 and 8 stands for the PNO selection thresholds of 10<sup>-7 </sup>and 10<sup>-8</sup>, which are used to produce the data under <strong>Table 11</strong> of the related publication.<br> </li> <li>The subdirectories <strong>CC.atz.f12</strong>, <strong>CC.dz</strong>, and <strong>CC.tz</strong> under<strong> </strong>C6H6* and C10H8* correspond to <strong>R(O)HF-CCSD(F12*)(T)/aug-cc-pVTZ</strong>, <strong>R(O)HF-CCSD(T)/cc-pvDZ </strong>and <strong>R(O)HF-CCSD(T)/cc-pvTZ </strong>calculations respectively, which is used for the calculation of the data under <strong>Table</strong> <strong>10</strong> of the related publication.<br> </li> <li>The subdirectories <strong>UHF-CC.atz.f12</strong> under C6H6-* and C10H8-* include <strong>UHF-CCSD(F12*)(T)/aug-cc-pVTZ </strong>calculations for the transition states and the products. The subdirectories <strong>CC.atz.f12 </strong>under C6H6 and C10H8 include <strong>RHF-CCSD(F12*)(T)/aug-cc-pVTZ</strong> calculations for the reactants benzene and naphthalene.<strong> </strong>These are used to calculate the data under <strong>Table 9</strong> in the related publication<br> </li> <li>The subdirectories <strong>rij.grid_m3.scfconv_7</strong> under C14H10* includes the DFT calculations with m3 integration grid and RI-J approximation. Under these, the subfolders <strong>(UHF-)PNO-CC.atz.f12</strong> include the <strong>PNO-(UHF-)CCSD(F12*)(T)/aug-cc-pVTZ</strong> calculations which are used to produce the data under <strong>Table 9</strong> in the related publication.<br> </li> <li>The subdirectories <strong>(UHF-)PNO-CC.atz.f12</strong> under C6H6* and C10H8* include<strong> PNO-(UHF-)CCSD(F12*)(T)/aug-cc-pVTZ</strong> calculations which are used for<strong> PNO threshold selection</strong> for the UHF-CCSD(F12*)(T) calculations (<strong>Table S2 </strong>of the Supporting Information of the related publication).</li> </ul>
Dataset associated to Untangling cooperative effects of pyridinic and graphitic nitrogen sites at metal-free N-doped carbon electrocatalysts for the oxygen reduction reaction
<p>This dataset contains the raw data for the published article "Untangling Cooperative Effects of Pyridinic and Graphitic Nitrogen Sites at Metal‐Free N‐Doped Carbon Electrocatalysts for the Oxygen Reduction Reaction". The dataset contains Electrochemistry, RAMAN and Xray photoelectron spectroscopy measures. This publication has emanated from research conducted with the financial support of Science Foundation Ireland under Grant No. 13/CDA/2213. J.A.B. acknowledges support from the Irish Research Council under Grant No. GOIPG/2014/399. This project has received funding from the European Union's Horizon 2020 Research and Innovation Programme under the Marie Skłodowska‐Curie grant agreements No. 748968 (FREMAB) and 799175 (HiBriCarbon). The results of this publication reflect only the authors' view and the Commission is not responsible for any use that may be made of the information it contains.</p>
Dataset associated to Electrocatalysis of N-doped carbons in the oxygen reduction reaction as a function of pH: N-sites and scaffold effects
<p>This dataset is associated to the following publication: "Electrocatalysis of N-doped carbons in the oxygen reduction reaction as a function of pH: N-sites and scaffold effects". It contains the raw data of the published article. This publication has emanated from research conducted with the financial support of Science Foundation Ireland under Grant No. <a href="https://www.sciencedirect.com/science/article/pii/S0008622319302763#gs1">13/CDA/2213</a>. JAB acknowledges support from the Irish Research Council under Grant No. <a href="https://www.sciencedirect.com/science/article/pii/S0008622319302763#gs2">GOIPG/2014/399</a>. This project has received funding from the European Union's Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreements No. 748968 (FREMAB) and 799175 (HiBriCarbon). The results of this publication reflect only the authors' view and the Commission is not responsible for any use that may be made of the information it contains.</p>
Datasets for "Insight into ductular reaction in obstructive biliary disease from a three-dimensional perspective using ex vivo X-ray phase contrast computed tomography"
<p>Phase-contrast CT of BDL rats liver-8 week</p>
Datasets for "Insight into ductular reaction in obstructive biliary disease from a three-dimensional perspective using ex vivo X-ray phase contrast computed tomography"
<p>Phase-contrast CT of BDL rats liver-6 week</p>
Datasets for "Insight into ductular reaction in obstructive biliary disease from a three-dimensional perspective using ex vivo X-ray phase contrast computed tomography"
<p>Phase-contrast CT of BDL rats liver-control group</p>
Datasets for "Insight into ductular reaction in obstructive biliary disease from a three-dimensional perspective using ex vivo X-ray phase contrast computed tomography"
<p>Phase-contrast CT of BDL rats liver-4 week</p>
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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.