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14 results for “exchange interaction”
Confined dipole and exchange spin waves in a bulk chiral magnet with Dzyaloshinskii-Moriya interaction-Data files
<p>Raw data associated to the manuscript ‘Confined dipole and exchange spin waves in a bulk chiral magnet with Dzyaloshinskii-Moriya interaction.” File formats are described in info.txt files in the concerning folders. For plotting and data evaluation Matlab 2019b and OriginPro 2018b were used. </p> <p>We acknowledge financial support from the Swiss National Science Foundation (SNSF) via Grant No. 171003 Sinergia project Nanoskyrmionics, the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) under Grant No. TRR80 (From Electronic Correlations to Functionality, Project No. 107745057, and Projects No. E1 and No. F7), SPP2137 (Skyrmionics, Project No. 403191981, Grant No. PF393/19), and the excellence cluster MCQST under Germany’s Excellence Strategy EXC-2111 (Project No. 390814868). Financial support by the European Research Council (ERC) through Advanced Grants No. 291079 (TOPFIT) and No. 788031 (ExQuiSid) is gratefully acknowledged.</p> <p>Paper abstract:</p> <p>The Dzyaloshinskii-Moriya interaction (DMI) has an impact on excited spin waves in the chiral magnet Cu<sub>2</sub>OSeO<sub>3</sub> by means of introducing asymmetry in their dispersion relations. The confined eigenmodes of a chiral magnet are hence no longer the conventional standing spin waves. Here we report a combined experimental and micromagnetic modeling study by broadband microwave spectroscopy, and we observe confined spin waves up to eleventh order in bulk Cu<sub>2</sub>OSeO<sub>3</sub> in the field-polarized state. In micromagnetic simulations we find similarly rich spectra. They indicate the simultaneous excitation of both dipole- and exchange-dominated spin waves with wavelengths down to (47.2 ± 0.05) nm attributed to the exchange interaction modulation. Our results suggest the DMI to be effective in creating exchange spin waves in a bulk sample without the challenging nanofabrication and thereby in exploring their scattering with noncollinear spin textures.</p>
Exploring the interaction of a curcumin azobioisostere with Abeta42 dimers using replica exchange molecular dynamics simulations
<p>Structural data and parameters relative to the evaluation of the interaction of an anti aggregating azobioisostere compound with the full-length Aβ42 peptide by replica-exchange molecular dynamics (REMD) simulations. Two different force fields (Amber and CHARMM) were used to simulate the azobioisostere-Abeta42 (AZ-Ab42) complex in a monomeric and dimeric assembly.</p> <p>A brief description of the shared output data is reported below:</p> <p><strong>1. Amber and CHARMM-adapted parameters for the simulated azobioisostere (AZ) compound.</strong></p> <p><strong>2. Modified version of the CHARMM36m FF - (CHARMM36mW)</strong></p> <p><strong>3. Starting (equilibrated) structures (first 5 T-replicas) for REMD on each of the following three systems (PDB): </strong></p> <ul> <li>Amber: AZ-Ab42 (monomeric ensemble): <strong>Repl.0 </strong>(315.0 K), <strong>Repl.1</strong> (316.7 K), <strong>Repl.2</strong> (318.4 K), <strong>Repl.3</strong> (320.1 K), <strong>Repl.4</strong> (321.8 K) </li> <li>Amber: AZ-Ab42 (dimeric ensemble): <strong>Repl.0</strong> (315.0 K), <strong>Repl.1</strong> (316.0 K), <strong>Repl.2</strong> (317.0 K), <strong>Repl.3</strong> (318.0 K), <strong>Repl.4</strong> (319.1 K) </li> <li>CHARMM: AZ-Ab42 (dimeric ensemble): <strong>Repl.0</strong> (315.0 K), <strong>Repl.1</strong> (316.0 K), <strong>Repl.2</strong> (317.0 K), <strong>Repl.3 </strong>(318.0 K), <strong>Repl.4</strong> (319.1 K)</li> </ul> <p><strong>4. Most populated clusters for the three simulated systems (PDB):</strong></p> <ul> <li>Amber AZ-Ab42 (monomeric ensemble): <strong>7</strong> clusters (<strong>Cl.0</strong>: 12.4%, <strong>Cl.1</strong>: 10.1%, <strong>Cl.2</strong>: 9.8%, <strong>Cl.3</strong>: 5.4%, <strong>Cl.4</strong>: 3.7%,<strong> Cl.5</strong>: 3.6%, <strong>Cl.6</strong>: 2.0%) </li> <li>Amber AZ-Ab42 (dimeric ensemble): <strong>5</strong> clusters (<strong>Cl.0</strong>: 7.1%, <strong>Cl.1</strong>: 4.3%, <strong>Cl.2</strong>: 3.5%,<strong> Cl.3</strong>: 3.2%, <strong>Cl.4</strong>: 2.4%) </li> <li>CHARMM: AZ-Ab42 (dimeric ensemble): <strong>3</strong> clusters (<strong>Cl.0</strong>: 4.7%, <strong>Cl.1</strong>: 4.6%, <strong>Cl.2</strong>: 2.5%) </li> </ul>
Neutron diffraction data for Magnetic ground state of NdB4: Interplay between anisotropic exchange interactions and hidden order on a Shastry-Sutherland lattice
<p>NdB4_NPD.zip contains TOF neutron powder diffraction patterns collected in the temperature range of 1.5K-100K</p> <p>journal_NdB4.pdf provides information about the NPD data collection temperature and run number</p>
Weak Exchange Interactions in Multispin Systems: EPR Studies of Metalloporphyrins Decorated with {Cr7Ni} Rings. Open data set
<p>Data supporting the original figures 2, 3, 4b, 5, and 6 of the related publication.</p>
Changing protein-DNA interactions promote ORC binding site exchange during replication origin licensing
<p><strong>Changing protein-DNA interactions promote ORC binding site exchange during replication origin licensing.</strong></p> <p>Zhang, Annie, Massachusetts Institute of Technology, ORCID: 0000-0003-3939-2585</p> <p>DOI: 10.5281/zenodo.7814499</p> <p>Primary publication DOI: <a href="https://doi.org/10.1073/pnas.2305556120">https://doi.org/10.1073/pnas.2305556120</a></p> <p> </p> <p><strong>Folder Structure</strong></p> <p> </p> <p>Source data are organized based on the parent figures from the main text (Figs 1-6). Source data from supplementary figures associated are placed within the associated parent figure folder. All figures, their associated parent figures, and the experiment names from which these figures are derived are summarized in the 'Summary.xlsx' file.</p> <p> </p> <p><strong>File Formats</strong></p> <p><strong> </strong></p> <p>1. Integrated trace files are saved as .dat files.</p> <p> </p> <p>- These trace files are obtained by integrating the fluorescence intensity contained within each DNA spot, or Area of Interest (AOI), over the range of the experimental time frame. They can be read and viewed in Matlab or the Matlab program imscroll, which is publicly available: <a href="https://github.com/gelles-brandeis/CoSMoS_Analysis">https://github.com/gelles-brandeis/CoSMoS_Analysis</a>.</p> <p> </p> <p>- Naming of files:</p> <p>The experiment name is specified at the beginning of the file name.</p> <p>The excitation and emission fields are specified using the following abbreviations.</p> <p>Gex: Green excited (Donor excited)</p> <p>Rex: Red excited (Acceptor excited)</p> <p>GexRex: Green and red excited (Donor and acceptor excited)</p> <p>Gem: Green emission (Donor emission)</p> <p>Rem: Red emission (Acceptor emission)</p> <p> </p> <p> </p> <p>To read the .dat integrated trace files in Matlab the user may type: </p> <p>>>[fn fp] = uigetfile</p> <p>% use the dialog box to mouse click on the appropriate *.dat file, then type:</p> <p>>>eval(['load ' [fp fn] ' -mat'])</p> <p>% This loads an aoifits structure array into the Matlab command environment</p> <p> </p> <p>The integrated trace data is stored in the aoifits.data matrix. A description of the columns is in the aoifits.dataDescription.</p> <p> </p> <p>The first five columns within aoifits.data are the most relevant to view fluorescence emission intensities at individual AOIs over time.</p> <p>Column 1: aoinumber</p> <p>Column 2: framenumber</p> <p>Column 3: amplitude (of fluorescence emission)</p> <p>Column 4: xcenter of the aoi</p> <p>Column 5: ycenter of the aoi</p> <p> </p> <p> </p> <p>2. Time Intervals are stored as excel spreadsheet (.xlsx) files.</p> <p> </p> <p>These files contain the AOI numbers used for analysis and frame numbers that correspond to specific events, such as protein arrival and departure events.</p> <p> </p> <p> </p> <p>3. For experiments with <em>E</em><sub>FRET</sub> analysis performed, <em>E</em><sub>FRET</sub> values are stored as .mat matrix files.</p> <p> </p> <p>Column 1: Time in seconds after protein colocalization with DNA</p> <p>Column 2: <em>E</em><sub>FRET </sub>values</p> <p>Column 3: AOI number</p> <p>Column 4: Frame number</p>
Figure source data for 'Ultrafast activation of the double-exchange interaction in antiferromagnetic manganites'
<p>This repository contains figure source data for 'Ultrafast activation of the double-exchange interaction in antiferromagnetic manganites'</p>
Data from: Cavity-mediated collective spin-exchange interactions in a strontium superradiant laser
Laser-cooled and quantum degenerate atoms are being pursued as quantum simulators and form the basis of today's most precise sensors. A key challenge toward these goals is to understand and control coherent interactions between the atoms. We observe long-range exchange interactions mediated by an optical cavity, which manifest as tunable spin-spin interactions on the pseudo spin-½ system composed of the millihertz linewidth clock transition in strontium. This leads to one-axis twisting dynamics, the emergence of a many-body energy gap, and gap protection of the optical coherence against certain sources of decoherence. Our observations will aid in the future design of versatile quantum simulators and the next generation of atomic clocks that use quantum correlations for enhanced metrology.
Data from: Woody plant biomass and carbon exchange depend on elephant-fire interactions across a productivity gradient in African savanna
Elephants and fire are individually well-known disturbance agents within savanna ecosystems, but their interactive role in governing tree-cover dynamics and savanna–forest biome boundaries remains unresolved. Of central importance are the mechanisms by which elephants vs. fire affect tree biomass and cover, and how – over long time periods – both factors interact with rainfall and soils to govern tree biomass and carbon dynamics. Here, we evaluated the response of woody vegetation to 56 years of fire manipulation in South Africa's Kruger National Park, with three fire regimes (annual, triennial and unburned) replicated across a productivity gradient and subject to two periods of contrasting elephant abundances (generated by the cessation of culling in 1994). Higher fire frequencies had a negative effect on woody biomass in the low-elephant period, but this effect was weak to negligible in the high-elephant period as the difference among fire treatments diminished. Moreover, elephants removed increasing amounts of woody biomass as productivity increased across study sites, but fire did not. We infer that elephant-induced tree mortality could overcome increases in woody-plant productivity, while fire-induced mortality alone could not. Elephants caused woody-plant carbon to shift from a sink to a source; this effect was independent of fire treatment, with highest rates of net carbon removal in the wettest and most productive site. Synthesis. Our results reveal a context-dependent interaction between fire and elephants as disturbance agents in savanna: the influence of fire on woody plants was sensitive to the abundance of elephants and diminished with increased plant productivity. In contrast, elephants were capable of shifting landscapes from relatively dense woodland to open savanna, even in unburned sites, and exerted strong impacts irrespective of site conditions and plant productivity.
Data from: Woody plant biomass and carbon exchange depend on elephant-fire interactions across a productivity gradient in African savanna
Open the record for dataset details and reuse information.
Data from: Pre-linguistic infants employ complex communicative loops to engage mothers in social exchanges and repair interaction ruptures
Open the record for dataset details and reuse information.
Data from: Cavity-mediated collective spin-exchange interactions in a strontium superradiant laser
Open the record for dataset details and reuse information.
Exchange of molecular and cellular information: a hybrid model that integrates stem cell divisions and key regulatory interactions [an3]
GEO Series GSE155462. Arabidopsis thaliana. 6 samples. Type: Expression profiling by high throughput sequencing.
Exchange of molecular and cellular information: a hybrid model that integrates stem cell divisions and key regulatory interactions [w5C6]
GEO Series GSE155463. Arabidopsis thaliana. 16 samples. Type: Expression profiling by high throughput sequencing.
Exchange of molecular and cellular information: a hybrid model that integrates stem cell divisions and key regulatory interactions
GEO Series GSE155464. Arabidopsis thaliana. 22 samples. Type: Expression profiling by high throughput sequencing.
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Allen Brain Atlas
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