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704 results for “Interference”
Synthesis of arbitrary interference patterns using a single galvanometric mirror
<h3>Version 1</h3> <p>CAD model</p> <p>Speed accessment images (images of fluorescent beads using 100 X microscope) and postprocessing code in MATLAB</p> <p>Laser interference images and postprocessing code in MATLAB</p> <ul> <li>Two beam and hexagonal pattern images were repeated multiple times</li> <li>Three beam images were taken at different axial positions</li> </ul> <p>2D SIM data with 100 nm fluorescent beads (two examples, <em>2D 1ms 980Hz 400mW.tiff </em>and <em>2D 1ms 980Hz 400mW.tiff</em>, not TIRF) and reconstruction code in MATLAB (<em>SIM_reconstrcution_2D.m</em>)</p> <ul> <li>Use <em>set_default_figure_parameters.m </em>to set the default figure unit to cm</li> <li>The camera jittered during the measurements. The images were shifted to cancel the jitter using <a href="https://uk.mathworks.com/matlabcentral/fileexchange/18401-efficient-subpixel-image-registration-by-cross-correlation">Efficient subpixel image registration by cross-correlation - File Exchange - MATLAB Central</a>. For comparison, two images are reconstructed, with and without cancelling the jitter </li> <li>Each set of measurement contain multiple cycles of 11 frames, of which the 4th and 8th frames are discarded</li> <li>Parameters are estimated using function <em>estimate_sim_parameters_KG.m</em></li> <li>Images are reconstructed using function <em>reconstruct_sim2_KG.m</em></li> <li>For reference, the images are averaged and have the PSF deconvolved using <em>deconv_Wiener_KG.m</em></li> </ul> <p>3D SIM data (<em>3D cell cropped.tiff), </em>widefield reference data (<em>WF cropped.tiff</em>) and reconstruction code in MATLAB (<em>SIM3D_cells.m</em>)</p> <ul> <li>Use <em>set_default_figure_parameters.m </em>to set the default figure unit to cm</li> <li>Parameters are estimated from a subset of the image (which has higher SNR) using function <em>estimate_sim_parameters_3D_KG.m</em></li> <li>Images are reconstructed using function <em>reconstruct_sim_3D_KG.m</em></li> <li>For reference, a widefield 3D image was captured by only illuminating the sample with one laser beam. The image is further processed using <em>WF3D_cells.m</em> and function <em>deconv_3D.m </em>to deconvolve the OTF</li> <li>The theorectial OTF is calculated using code from <a href="https://github.com/jdmanton/debye_diffraction_code">https://github.com/jdmanton/debye_diffraction_code</a> which is included in the package</li> </ul> <h3>Version 2</h3> <p>2D TIRF SIM data with 100 nm fluorescent beads (same as Version 3) and reconstruction code in MATLAB. I forgot to upload background noise image. Please use Version 3 to avoid error in running the code</p> <h3>Version 3 </h3> <p>2D TIRF SIM data with 100 nm fluorescent beads (same as Version 2) and reconstruction code including FRC in MATLAB (<em>main.m</em>)</p> <ul> <li>Use <em>set_default_figure_parameters.m </em>to set the default figure unit to cm</li> <li>Raw data include two sets of measurements (<em>TIRF beads.tiff and TIRF beads 2.tiff</em>) and background noise image (<em>bg 1ms.tiff</em>)</li> <li>Each set of measurement (e.g. <em>TIRF beads.tiff</em>) contain two cycles of 11 frames, of which the 4th and 8th frames are discarded in each cycle</li> <li>Parameters are estimated using function <em>estimate_sim_parameters_KG.m</em></li> <li>Images are reconstructed using function <em>reconstruct_sim2D_KG.m</em></li> <li>For reference, the images are averaged and have the PSF deconvolved using <em>deconv_Wiener_KG.m</em></li> </ul> <p>3D SIM data (same as Version 1) and reconstruction code for FRC in MATLAB (<em>main.m</em>)</p> <ul> <li>Use <em>set_default_figure_parameters.m </em>to set the default figure unit to cm</li> <li>Two subsets of the image were taken for FRC, one with even z steps and one with odd z steps</li> <li>Parameters are estimated using function <em>estimate_sim_parameters_KG.m</em></li> <li>Images are reconstructed using function <em>reconstruct_sim2D_KG.m</em></li> <li>The two subsets are reconstructed independently (double z step size) and the centre z position of each image are used to calculate FRC</li> <li>Only subsets of the image are processed. Refer to Version 1 for larger range in z.</li> </ul> <p>Stability accessment images (two beam laser interference images taken over periods of time) and postprocessing code in MATLAB</p> <p>2D SIM (not TIRF) data with 200 nm fluorescent beads measured over the full FOV and reconstruction code in MATLAB</p> <ul> <li>Processed in almost the same way as 2D TIRF SIM</li> <li>Parameters were estimated using the centre of the FOV</li> <li>Sections with ~10 um horizontal distances are plotted to show change of quality across the FOV</li> </ul> <p>PSF data measured using 200 nm fluorescent beads and postprocessing code in MATLAB</p> <ul> <li>Individual bead images are picked and fit with theoretical PSF function to obtain resolution</li> <li>Beads with ~10 um horizontal distances are plotted to show change of quality across the FOV</li> </ul>
Fig. 2 in Interference Competition and Cannibalism by Dorcus rectus(Motschulsky) (Coleoptera: Lucanidae) Larvae in the Laboratory and Field
Fig. 2. Relationship between larval density of Dorcus rectus in decaying willow trunks and the intensity of intraspecific interference in the field. Each circle represents an examined trunk. Trunks with one to four larvae were excluded from this figure because the results for one larva would have changed the percentage of wounded larvae greatly by 25–100%.
Competition for food affects the strength of reproductive interference and its consequences for species coexistence.
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Data from: the two faces of secondary contact on islands: introgressive hybridization between endemics and reproductive interference between endemics and introduced species
<p>Aim: Hybridization is thought to have played an important role in shaping the evolutionary history of diverse island taxa. Here, we propose an ecological and evolutionary framework for understanding the causes and consequences of heterospecific mating on islands – with and without introgressive hybridization. We use this framework to support our main contention that cases of secondary contact among endemic species should commonly result in introgressive hybridization whereas cases of contact between endemic and introduced species should commonly result in reproductive interference – resulting in two qualitatively different faces of secondary contact on islands.</p> <p>Location: Canary Islands, Galapagos, New Zealand, Caribbean, and Hawaii.</p> <p>Taxa: 705 vertebrate, invertebrate, and plant species spanning 167 genera and 99 families.</p> <p>Methods: Using a quantitative analysis of empirical research on secondary contact on islands, we weigh evidence for the drivers of secondary contact and heterospecific mating on islands. In particular, we compare cases of secondary contact between endemic species versus secondary contact between endemic and introduced species.</p> <p>Results: We find that three main drivers of secondary contact and heterospecific mating on islands most frequently reported in the literature are disturbance, long-distance (e.g. inter-island) dispersal, and compromised assortative mating. We find support for the hypothesis that introgression is a more common outcome between endemic species while reproductive interference is a more common outcome between endemic and introduced species.</p> <p>Main conclusions: We conclude that there are biological reasons to predict secondary contact and heterospecific mating to be common on islands for all taxa, but that the consequence of secondary contact is categorically different for contact between endemic species and contact between endemic and introduced species. We conclude that the former likely explains the apparent frequency of hybridization on islands, while the latter presents a cryptic and underappreciated conservation threat.</p>
Dataset for "Three-dimensional spin-wave dynamics, localization and interference in a synthetic antiferromagnet"
<p>Data availability for the article titled "Three-dimensional spin-wave dynamics, localization and interference <br>in a synthetic antiferromagnet" by Girardi et al. published in Nature Communications.</p> <p>This data repository contains the following folders and files:<br>• TR Lamni Raw Data - Co: Files with extension .hdf5 are Time-Resolved Soft X-Ray Laminography Raw Data for all projections acquired to obtain the 3D reconstruction for the CoFeB layer. The projections’ data have been organized in sub-folders for the 7 frames acquired during the measurements. For each frame, a final folder “analysis” contains an aligned_projection.mat file with the angles of all measured projections and the sinogram information.<br>• TR Lamni Raw Data - Ni: Files with extension .hdf5 are Time-Resolved Soft X-Ray Laminography Raw Data for all projections acquired to obtain the 3D reconstruction for the NiFe layer. The projections’ data have been organized in sub-folders for the 7 frames acquired during the measurements. For each frame, a final folder “analysis” contains an aligned_projection.mat file with the angles of all measured projections and the sinogram information.<br>• Magnetic reconstruction – Ni edge: contains the .mat files of the 3D magnetic reconstruction obtained for Ni-edge for all 7 frames. In each file, the Mx, My and Mz components of the magnetization associated with the 3D reconstruction of the volume of the sample are present. <br>• Magnetic reconstruction – Co edge: contains the .mat files of the 3D magnetic reconstruction obtained for Co-edge for all 7 frames. In each file, the Mx, My and Mz components of the magnetization associated with the 3D reconstruction of the volume of the sample are present. <br>• vtk files: contains the post-processed files for all 7 frames in the .vtk format for the 3D visualization with the Paraview software. In each file, both vectorial and scalar data associated with the 3D reconstruction of the volume of the sample and analyzed in the paper are present.<br>• Mumax3 simulation dispersion relation: contains .ovf files (containing information about the Mx, My, Mz components of the magnetization as a function of the spatial position) obtained from the mumax3 simulation to study the spin wave dispersion relation of the sample investigated. The total simulation runtime is 10 ns, and each .ovf file corresponds to a frame saved every 0.01 ns.<br>• Mumax3 simulation 3D interference: contains the .ovf files (containing information about the Mx, My, Mz components of the magnetization as a function of the spatial position) for the static magnetization and 3 frames used to simulate the 3D interference pattern observed experimentally. </p>
"Entanglement-induced collective many-body interference": supporting raw data
<p>Dataset for the manuscript "Entanglement-induced collective many-body interference" (<a href="https://arxiv.org/abs/2310.08630" target="_blank" rel="noopener">arXiv:2310.08630</a>).</p> <p>The dataset comprises .csv files containing measurements relevant to supporting the manuscript. Enclosed within the <strong>ECMBI.zip</strong> file are two primary folders:</p> <ol> <li> <p><strong>CoincidencesDataSet:</strong> This directory contains subdirectories with raw data supporting single and coincidence count rates.</p> <ul> <li> <p><strong>Coincidences_PsiMinus:</strong> Polarization-entangled state set to the Bell state ψ- as specified in the manuscript. The directory includes the following subdirectories:</p> <ul> <li><strong>Source1:</strong> Contains 48 CSV files of 60-second count rate measurements, sorted chronologically, when only the first photon source (Source 1) is employed. Each file contains count rate measurements for 31 different settings of the input polarization state. Within the set of 48 files, 16 files contain single-count and four-fold coincidence rates, 16 files contain three-fold coincidence rates, and 16 files contain two-fold coincidence rates. Half of the 48 files are corrected for multipair emissions (denoted by an additional Nin the file name: "*FoldN_*.csv") by rejecting events where there are coincidences in k>4 detectors (a total of 8 detectors is used).</li> <li><strong>Source2:</strong> Contains 48 CSV files of 60-second count rate measurements, sorted chronologically, when only the second photon source (Source 2) is employed. Similar to Source1, it comprises 16 files for single-count and four-fold coincidence rates, 16 files for three-fold coincidence rates, and 16 files for two-fold coincidence rates. Again, half of the 48 files are corrected for multipair emissions (denoted by an additional N in the file name: "*FoldN_*.csv").</li> <li><strong>Source1Source2:</strong> Contains 120 CSV files of 60-second count rate measurements, sorted chronologically, when both photon sources (Source 1 and Source 2) are employed. Similar to the Source1 and Source2 folders, it consists of 40 files for single-count and four-fold coincidence rates, 40 files for three-fold coincidence rates, and 40 files for two-fold coincidence rates. Once more, half of the 120 files are corrected for multipair emissions (denoted by an additional N in the file name: "*FoldN_*.csv").</li> </ul> </li> <li> <p><strong>Coincidences_PsiPlus:</strong> Polarization-entangled state set to the Bell state ψ+ as specified in the manuscript. The structure mirrors that of Coincidences_PsiMinus.</p> </li> </ul> </li> <li> <p><strong>TomographyDataSet:</strong> This folder contains raw data supporting the fidelity measurement of the polarization-entangled states ψ+ and ψ-. Two tomography stages are used to perform measurements in 36 distinct combinations of the two detectors' measuring polarization basis (e.g., H, H; H, V; H, D; H, A; H, R; H, L; V, H; etc.).</p> <ul> <li><strong>Tomography_PsiMinus:</strong> Polarization-entangled state set to the Bell state ψ-. The directory contains 6 CSV files for 6 different pumping power levels, each measuring 5-second two-fold coincidence rate for all 36 polarization bases.</li> <li><strong>Tomography_PsiPlus:</strong> Polarization-entangled state set to the Bell state ψ+. The directory content mirrors Tomography_PsiMinus.</li> </ul> </li> </ol>
FIGURE 89. Wing interference patterns. A–B in New Mythicomyia Coquillett, 1893 (Diptera: Mythicomyiidae: Mythicomyiinae) from Peru
FIGURE 89. Wing interference patterns. A–B. Mythicomyia huk sp. nov., C–D. Mythicomyia iskay sp. nov., E–F. Mythicomyia kinsa sp. nov.
FIGURE 90. Wing interference patterns. A–B in New Mythicomyia Coquillett, 1893 (Diptera: Mythicomyiidae: Mythicomyiinae) from Peru
FIGURE 90. Wing interference patterns. A–B. Mythicomyia tawa sp. nov., C–D. Mythicomyia pisqa sp. nov.
Minimising feeding behaviour interference: a Hay-Shaker device to assess dust exposure in horses
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Fano interference in quantum resonances from angle-resolved elastic scattering
<p>This is source data for the figures in the publication "Fano interference in quantum resonances from angle-resolved elastic scattering".</p>
Data of Control of reactive collisions by quantum interference
<p>One can find:</p> <p>(1) The tabulated data for every plot in the main article and the supplemental material of 'Control of reactive collisions by quantum interference.'</p> <p>(2) The jupyter notebook file (Python2) and raw data to reproduce the plots. Open 'ProcessData_FINAL.ipynb' and excute the cell sequentially, after excuting the three cells at the end first to properly define functions.</p>
Figure 5 in Evidence for vocal diversity during physical interference at the perch in sympatric Carollia species (Chiroptera: Phyllostomidae): a key to social organization and species coexistence?
Figure 5. Cluster analysis of class usage per dyad during physical interference at the perch, based on Euclidean distances. Each symbol represents a specific dyad. The x-axis represents the three clusters set by k-means clustering to which a given dyad was sorted; the y-axis represents the species to which a given dyad belonged, and the z-axis represents the relative distances of each dyad from the respective cluster centre. Dyad sex composition (passive bat is given second) is indicated by different symbols, with the sex of the passive bat indicated by different colours (in red–pink dyads, the passive bat is female; in blue–turquoise dyads it is male). Note that most dyads of a given species grouped in a specific cluster, whereas no clear pattern was found for dyad sex composition or sex of the passive bat.
Figure 4 in Evidence for vocal diversity during physical interference at the perch in sympatric Carollia species (Chiroptera: Phyllostomidae): a key to social organization and species coexistence?
Figure 4. The frequency of occurrence of a class across interactions is represented by different colours for Carollia castanea (Cc), Carollia sowelli (Cs) and Carollia perspicillata (Cp). Of the 21 classes discriminated, 20 occurred in C. castanea, 12 in C. perspicillata and five in C. sowelli. The high vocal variability of C. castanea is highlighted by the presence of six rarely occurring classes specific for this species, summarized as other. Please note that class dms, selected for comparative analyses, occurred frequently across all species.
Figure 3 in Evidence for vocal diversity during physical interference at the perch in sympatric Carollia species (Chiroptera: Phyllostomidae): a key to social organization and species coexistence?
Figure 3. Oscillograms (upper panels) and sonagrams (lower panels) representing down-sweeps (sensu Knörnschild et al., 2013) emitted by the three sympatric Carollia species present at Hitoy Cerere, Costa Rica. A, C, E, parts of a dms bout of Carollia castanea (A), a dms bout of Carollia sowelli (C) and a dms bout of Carollia perspicillata (E) are given. B, D, F, for comparison, two ds syllables of C. castanea (B), two of C. sowelli (D) and four of C. perspicillata (F) are shown. Note that syllable durations and time intervals between syllables are quasi-constant within dms bouts and more variable for sequences of ds syllables.
Figure 2 in Evidence for vocal diversity during physical interference at the perch in sympatric Carollia species (Chiroptera: Phyllostomidae): a key to social organization and species coexistence?
Figure 2. Oscillograms (upper panels) showing the relative amplitude (rel. amp.) and sonagrams (lower panels) representing typical frequency–time contours of vocalization classes associated with the social interaction of Carollia bats landing on, grabbing or hanging on a perched conspecific: warbles (A), down-sweep-warble (B), U (C), sinus (D), convex downwardmodulated (E), a dms syllable followed by upward-modulated-sweep (F), other_6 (G), other_1 (H) followed by other_2 (I), U-warbles (J), shallow-U (K), other_3 (L) followed by flat-down-sweep (M), sinus-warble (N) and other_4 (O). A and B are examples from Carollia perspicillata; other examples are from Carollia castanea.
Figure 1 in Evidence for vocal diversity during physical interference at the perch in sympatric Carollia species (Chiroptera: Phyllostomidae): a key to social organization and species coexistence?
Figure 1. Phylogenetic tree for species of the genus Carollia. Genus Rhinophylla served as an outgroup. The numbers above branches are posterior probability estimations. Note how the individuals of the study cluster together in the correct species. Carollia perspicillata are indicated in orange, Carollia sowelli in green and Carollia castanea in yellow.
Figure 6 in Evidence for vocal diversity during physical interference at the perch in sympatric Carollia species (Chiroptera: Phyllostomidae): a key to social organization and species coexistence?
Figure 6. Species discrimination based on a discriminant function analysis of acoustic parameters of dms syllables. Median values for each dyad were used in the analysis. The two discriminant functions (DF1 and DF2) are given with the percentage of variance explained. Carollia castanea (Cc) is represented by circles, Carollia sowelli (Cs) by triangles and Carollia perspicillata (Cp) by squares. The corresponding centroids are shown with a bigger symbol. For each species, 95% confidence ellipses are also plotted.
The parameters of the anti-interference time-frequency slices
<p> In the time-frequency domain, two code element signals with minimal correlation are designed, which represent binary "0" and "1" respectively to transmit information. The anti-interference time-frequency slice modulation method using seismic vibrators may be used for underground emergency communication.</p>
Understanding and Mitigating the Impact of Wi-Fi 6E Interference on Ultra-Wideband Communications and Ranging
<p>Artifacts containing data sets and scripts for the paper "Understanding and Mitigating the Impact of Wi-Fi 6E Interference on Ultra-Wideband Communications and Ranging" published at the <em>International Conference on Information Processing in Sensor Networks </em>(IPSN) 2022.</p>
Critical Period of Weed Interference_Lettuce_AV_Raw Data
<p>The data has been uploaded as supporting information to the article accepted for publication in the journal Horticolturae. </p>
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