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1,184 results for “conversion”
Figure 5 in Impact of rainforest conversion into monoculture plantation systems on pseudoscorpion density, diversity and trophic niches
Figure 5. Stable isotope values of pseudoscorpion species in different land-use systems; means with standard deviation. Dashed horizontal lines represent estimated trophic level boundaries; trophic level 1 (plant material) not shown. Decomposers feeding on detritus (trophic level 2) were assumed to be enriched in 15N by 1.7 ‰ compared to leaf litter, each following trophic level was assumed to span 3.4 ‰ (Post 2002; Potapov et al. 2019a). For abbreviations see Table 1.
Figure 3 in Impact of rainforest conversion into monoculture plantation systems on pseudoscorpion density, diversity and trophic niches
Figure 3. Bootstrap species accumulation curve based on the number of adult individuals in the studied land-use systems.
Figure 4 in Impact of rainforest conversion into monoculture plantation systems on pseudoscorpion density, diversity and trophic niches
Figure 4. Venn diagram of the species composition in the three land-use systems studied (rainforest, rubber, oil palm) in the Bukit Duabelas (left) and Harapan landscape (right). Landscape-specific species are underlined in red. The riparian-specific species in Harapan is underlined in cyan. For abbreviations see Table 1.
Figure 2 in Impact of rainforest conversion into monoculture plantation systems on pseudoscorpion density, diversity and trophic niches
Figure 2. Density of pseudoscorpions in litter and soil of the three land-use systems studied (rainforest, rubber, oil palm) in the Bukit Duabelas and Harapan landscape. Each data point represents one sampling plot (three pooled subplot samples). Only non-riparian sites are shown.
Figure 1 in Impact of rainforest conversion into monoculture plantation systems on pseudoscorpion density, diversity and trophic niches
Figure 1. Four species of pseudoscorpions found at the study sites. From left to right: Atemnidae sp.1, Lagynochthonius sp.1, Atemnidae sp.2, Hya minuta.
Localized Topological States beyond Fano Resonances via Counter-Propagating Wave Mode Conversion in Piezoelectric Microelectromechanical Devices
<p>Main numerical and experimental data (Matlab .fig files) of the paper <em>Localized Topological States beyond Fano Resonances via Counter-Propagating Wave Mode Conversion in Piezoelectric Microelectromechanical Devices.</em></p>
Text to Rule Conversion Full Results for Anirudh Prabhu's PhD Dissertation
<p>Part of Anirudh Prabhu PhD Dissertation. Contains the results of running the text to rule conversion workflow described in chapter 5 of the dissertation. The dataset preview and its description can be found in Appendix E of the dissertation document. </p>
Raw data files for the manuscript entitled "Understanding your support system: the design of a stable MOF/polyazoamine support for biomass conversion"
<p>Raw data files for the manuscript entitled "Understanding your support system: the design of a stable MOF/polyazoamine support for biomass conversion" published in Chemistry of Materials. <a href="https://doi.org/10.1021/acs.chemmater.2c01731">https://doi.org/10.1021/acs.chemmater.2c01731</a></p> <p>The files are organized by manuscript figure names and are in a simple text format. The headers contain the necessary information such as column designations.</p>
Model setup and output for 'Tidal conversion and dissipation at steep topography in a channel poleward of the critical latitude'
<p><strong>Data supplement to Hughes and Klymak 2019</strong></p> <p>Model input and output in a reduced form associated with the following paper:</p> <p><strong>Tidal conversion and dissipation at steep topography in a channel poleward of the critical latitude<br></strong><em>Journal of Physical Oceanography.</em> <a href="http://dx.doi.org/10.1175/JPO-D-18-0132.1">doi:10.1175/JPO-D-18-0132.1</a></p> <p><strong>Inputs</strong></p> <p>As described in Table 1 of the associated paper, there are three main sets of simulations. The input files for these sets are contained in their respective directories (`vary_width`, `vary_forcing`, and `vary_freq`). The python script that creates all of the necessary files is `gendata.py`. A fourth directory is titled `baroclinic_terms` and includes that simulation in which <em>u'</em> and <em>p'</em> are output at high temporal resolution.</p> <p>A key point regarding the input files is that for the vary width and vary forcing cases, a single simulation involves multiple channels. This lets me compile a single executable `mitgcmuv` with a Nx × Ny grid of 600 × 1280, which I divide up into the necessary number of channels by putting vertical walls in appropriate places. For the vary width cases, the 'narrow' simulations are all channels from 0.2 to 32 km and the 'wide' simulations are all wider channels. Once the simulation has run, I use netcdf tools (`ncks`) to extract the individual channels using the scripts in the `extract_scripts` directory.</p> <p>Most of the files in the `code` directories will be familiar to anyone that uses the MITgcm. An exception is the `energy_diagnostics_fill.F` (and `diagnostics_main_init.F` and `do_statevars_diags.F`, which have minor additions). The original, from `https://github.com/jklymak/MITgcmcode`, was modified slightly to suit this project.</p> <p><strong>Outputs</strong></p> <p>The results directory contains five subdirectories to be described in turn.</p> <p>Notes that in all cases, energy terms in the netCDF files do not include a factor of ρ. This was added in at the plotting stage.</p> <p>All simulations used Checkpoint67b and were run on Graham: https://docs.computecanada.ca/wiki/Graham.</p> <p><strong>vary_width</strong></p> <p>The majority of the files are of the form `obstacle_FFF_YY.nc` where `FFF` is $1000 ω/f$ and `YY` is the channel width in kilometres. These files contain the tidally averaged, depth-integrated energy diagnostics for the seventh tidal cycle at all points (<em>x, y</em>) within the energy control volume.</p> <p>There are also three files entitled `tophat_995_YY.nc`, which contain fields of <em>U</em>, <em>V</em>, and <em>T</em> (which gives density with α = 0.0002) at two levels. These fields are used as examples for weakly and strongly responding channels.</p> <p><br><strong>vary_forcing</strong></p> <p>These files are of the form `forcing_UU.nc` where `UU` is the deep-water tidal current amplitude <em>U_</em>0 in cm/s. They contain the same energy terms as for the vary width simulations.</p> <p><strong>vary_freq</strong></p> <p>These files are of the form `freq_FFF_fields.nc` and contain fields of <em>U</em>, <em>V</em>, and <em>T</em> at two levels. Energy terms are not included because the vary frequency simulations were only run to get estimates of the along-ridge wavelength.</p> <p><strong>baroclinic_terms</strong></p> <p>The single file within this directory contains <em>u'</em> and <em>p'</em> at a single <em>x</em> position every five minutes for four tidal cycles.</p> <p><strong>gaussian_26</strong></p> <p>This directory, named for its obstacle and width, contains <em>U</em>, <em>V</em>, and <em>T</em> at every grid point for a snapshot in time and another file with the corresponding snapshots of all energy terms.</p>
Data for: Tailored frequency conversion makes infrared light visible for streak cameras
<p>Data for the publication "Tailored frequency conversion makes infrared light visible for streak cameras".</p> <p>Streak cameras are one of the most common and convenient devices to measure pulsed emission e.g. from semiconductor lightsources with picosecond time resolution. However, they are most sensitive in the visible range and possess low or negligible efficiency in the infrared and telecom regime. In this work, we present a frequency conversion based on sum-frequency generation that converts infrared to visible signals while preserving their temporal properties, making them detectable with a streak camera. We demonstrate and verify the functionality of our device by converting the emission from a quantum dot laser.</p> <p>Funded by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) – SFB-Geschäftszeichen TRR142/3-2022 – Projektnummer 231447078, Project C01.</p>
Conversion from forest to agriculture in the Brazilian Amazon from 1985 to 2021
<p>This file collection contains data with conversion length from forests to agriculture in the Brazilian Amazon, from 1985 to 2021. Calculations were based in the MapBiomas thematic maps. More information can be found in the repository website (<a href="https://github.com/hugotseixas/forest-agri-conversion/tree/3.0.0">https://github.com/hugotseixas/forest-agri-conversion/tree/3.0.0</a>).</p> <p>The collection is composed of six sets of data:</p> <p><strong>c_raster_mosaic</strong>: raster files of the Amazon biome with values of conversions;</p> <p><strong>c_raster_tiles</strong>: raster files of smaller raster tiles, with values of conversions;</p> <p><strong>c_tabular_dataset</strong>: a group of tables that contains data about conversions;</p> <p><strong>figures</strong>: data to create figures of the manuscript;</p> <p><strong>raw_raster_tiles</strong>: raster files of smaller raster tiles with land use and land cover classification data from MapBiomas;</p> <p><strong>validation</strong>: data used to performed validation of the conversion results.</p>
Data files of the paper "Energy conversion by magnetic reconnection in multiple ion temperature plasmas"
<p>Reconnection rate and energy budget files for the simulations used in for the paper "Energy conversion by magnetic reconnection in multiple ion temperature plasmas". The paper has two simulations. The first one, without cold ions, has his reconnection rate data stored in "rate_147.dat" and the energy budget data in "Ebudget_symm_nocold_Xframe.h5". The second one, with cold ions, has his reconnection rate data stored in "rate.dat" and the energy budget data in "Ebudget_symm_cold_Xframe.h5".</p> <p>On top of that is a datafile from simulation 1 at time 144.5 (corresponding to the time of the picture A in figure 1) with all the output fields from the simulation at this given time.</p>
Deciphering methylation effects on S2(ππ∗) internal conversion in the simplest linear α,β-unsaturated carbonyl
<p>Here you will find the dataset related to the article entitled: Deciphering methylation effects on S2(ππ∗) internal conversion in the simplest linear α,β-unsaturated carbonyl.</p> <p>------------------------------------------------------------------------------</p> <p><strong>critical_points_geometries.zip</strong></p> <p>This repository contains the XYZ files of the critical points computed at the hh-TDA-ωPBEh/6-31G(d,p) (hh-TDA) and SA5-XMS(Im=0.3)-CASPT2(10,9)/cc-pVDZ (XMSPT2) levels of theory. Also, exmaple input files for MECI and geometry optimizations for TeraChem (hh-TDA level) and BAGEL (XMS-CASPT2).</p> <p>Notation:</p> <ul> <li>AC - Acrolein </li> <li>CR - Crotanaldehyde</li> <li>MVK - Methylvinylketone </li> <li>MA - Methacrolein </li> <li>S0min - Minimum of S0 electronic state</li> <li>S1min - Minimum of S1 electronic state</li> <li>S2min - Minimum of S2 electronic state</li> <li>S1S0_MECI - Minimum energy conical intersection at S1 and S0 electronic states intersection</li> <li>S2S1_MECI - Minimum energy conical intersection at S2 and S1 electronic states intersection</li> <li>NTpyr, CCpyr, N.... relates to the label of different MECI structures. Information regarding this nomenclature can be found in the Supporting Information of the paper.</li> </ul> <p>Computational details and extra information regarding these structures can be found in the main text and supporting information of the article. </p> <p>------------------------------------------------------------------------------------------------------------------------------------------</p> <p><strong>AIMS_ICs.zip</strong></p> <p>This repository contains all the initial conditions (ICs) sampled to perform the ab-initio multiple spawning dynamics simulations for acrolein (AC), crotanaldehyde (CR), methylvinylketone (MVK), and methacrolein (MA).</p> <p>For AC, CR, MVK and MA, 50 ICs were randomly sampled from a narrow window of 0.05 eV around 6.20 eV (from the calculated absorption spectra)</p> <p>For CR, 10 additional ICs were also sampled in addition to the 50, to ensure that the observed stalling in population decay around 600-900fs in not due to undersampling.</p> <p>All IC files are named as ICXXXX.dat where XXXX = randomly selected IC number</p> <p>Each IC file contains the cartesian coordinates in Bohr and the corresponding nuclear velocities in Bohr/atomic unit.</p>
Core-Hole Spectroscopy of Energy Conversion and Storage Related-Phosphorus Compounds Using Soft and Hard X rays
<p>Dear reader,</p> <p> </p> <p>Please find attached the input files (.xml) and their corresponding outputs for the Exciting calculations of the imaginary component of the dielectric tensor ("XAS".dat) for: InP, GaP, red P and InPO4 which have been used in our publication:"Core-Hole Spectroscopy of Energy Conversion and Storage Related-Phosphorus Compounds Using Soft and Hard X rays". </p>
Core-Hole Spectroscopy of Energy Conversion and Storage-Related Phosphorus Compounds Using Soft and Hard X rays (Experimental XANES dataset)
<p>Dear readers,</p> <p>In the following, we provide the complete experimental X-ray absorption near-edge structure (XANES) spectroscopy dataset given in our investigation of: "Core-Hole Spectroscopy of Energy Conversion and Storage Related-Phosphorus Compounds Using Soft and Hard X-rays". This dataset includes partial fluorescence yield (PFY)-XANES at P <em>K</em>-edge and P <em>L</em><sub>2,3</sub>-edge of 9 solid P-containing compounds with different chemical environments and oxidation states ranging from P(-III) to P(V), namely: GaP, InP, red phosphorus (Red-P), H<sub>3</sub>PO<sub>3</sub>, Na<sub>2</sub>H<sub>2</sub>P<sub>2</sub>O<sub>6</sub>, H<sub>3</sub>PO<sub>4</sub>, KH<sub>2</sub>PO<sub>4</sub>, Na<sub>2</sub>HPO<sub>4</sub>, InPO<sub>4</sub>. Additionally, P <em>K</em>-edge XANES spectra of aqueous P-containing acids: 1 mol dm<sup>-3</sup> H<sub>3</sub>PO<sub>4</sub>, 1 mol dm<sup>-3</sup> H<sub>3</sub>PO<sub>3</sub>, as well as the solution mixture of 1 mol dm<sup>-3</sup> H<sub>3</sub>PO<sub>3</sub> + 1 mol dm<sup>-3</sup> H<sub>3</sub>PO<sub>4</sub>, and 0.1 mol dm<sup>-3</sup> H<sub>3</sub>PO<sub>3</sub> + 1 mol dm<sup>-3</sup> H<sub>3</sub>PO<sub>4</sub>.</p>
Data from: Rainforest conversion to plantations fundamentally alters energy fluxes and functions in canopy arthropod food webs
<p><span>Tropical rainforests around the world are rapidly being converted into cash-crop agricultural systems. The associated massive losses of plant and animal species lead to changes in arthropod food webs and the energy fluxes therein. These changes are poorly understood, in particular in the extremely biodiverse canopies of tropical ecosystems. Using canopy fogging followed by stable isotope and energy flux analyses, we show that land-use conversion from rainforest to rubber and oil palm plantations not only causes a drastic reduction in energy fluxes of up to 75% but also shifts fluxes among trophic groups. While rainforests featured high levels of both herbivory and algae-microbiology, and a balanced ratio of herbivory to predation, relative fluxes were shifted towards predation in rubber and towards herbivory in oil palm plantations, indicating profound shifts in ecosystem functioning. Our results highlight that the ongoing loss of animal biodiversity and biomass in tropical canopies degrades animal-driven functions and restructures canopy food webs.</span></p>
Reflective Microscopy Dataset on the Formation of Zr-Based Conversion Coating on Al2024
<p>The accompanying files contain the raw optical images and initial data processing results, conducted in Python environments, related to the spontaneous formation of a Zirconium-based conversion coating (CC) on an Al2024 alloy.</p> <p>The files designated as 16-47-51.761.zip and similar, contain the raw optical images that chronicle the continuous observation of CC formation over a span of up to 40 minutes. The naming convention of these files is representative of the hours-minutes-seconds.milliseconds timestamp when the data recording began.</p> <p>Image capture commenced at a rate of 5 frames per second (Hz), and subsequent images were acquired at a rate of 1 Hz. This timestamped naming approach also extends to the individual raw images, reflecting the precise time at which each image was taken. Each image measures 2000x2000 pixels, with an individual pixel resolution of 240 nanometers and a pixel depth of 12 bit.</p> <p>The file labeled Image_processing.ipynb is a Jupyter lab notebook containing the image processing routine, implemented in Python 3 programming language. A PDF version of this notebook, for ease of printing and viewing, is available in the file named IMAGE_PROCESSING.pdf. This script has generated a selection of images and videos, which can be found within the Generated_images.zip and Generated_videos.zip folders.</p> <p>The normalized_intensity.png file contains the most pivotal plot, which displays the normalized intensity as a function of time. This graph is designed to reflect the progression of the CC thickness, interpreted through Fresnel equations.</p> <p>The video files provide unedited footage of the first 3 minutes of the Al surface's exposure to the CC solution, along with the normalized data. A side-by-side comparison of raw and normalized data for a 300x300 pixel image cut is also available in these video files.</p>
Dataset: Evaluating approximate asymptotic distributions for fast neutrino flavor conversions in a periodic 1D box
<p>In this data package we include two txt files and two zip files.</p> <p>The file Gaussian.txt contains 4 columns. The first column shows the indices of the file numbers contained in the file Gaussian_100.zip. The second, third, and fourth columns list the corresponding <span class="math-tex">\(I_{\bar\nu}\)</span>, <span class="math-tex">\(F_\nu\)</span>, and <span class="math-tex">\(F_{\bar\nu}\)</span>, respectively. </p> <p>The file Maxent.txt contains 5 columns. The first column shows the indices of the file numbers contained in the file Maxent_100.zip while the second column lists the corresponding indices in the file Gaussian.txt. The third, fourth, and fifth columns list the corresponding <span class="math-tex">\(I_{\bar\nu}\)</span>, <span class="math-tex">\(F_\nu\)</span>, and <span class="math-tex">\(F_{\bar\nu}\)</span>, respectively. </p> <p>Files Gaussian_100 and Maxent_100 give the asymptotic simulated outcomes of fast neutrino flavor conversions with the initial Gaussian and maximum-entropy distributions, respectively. Each data file xxxx.dat lists four columns for <span class="math-tex">\(v_z\)</span>, <span class="math-tex">\(P_{ee}(v_z)\)</span>, <span class="math-tex">\(g_\nu(v_z)\)</span>, and <span class="math-tex">\(g_{\bar\nu}(v_z)\)</span>, respectively. We take 100 <span class="math-tex">\(v_z\)</span> grids for all data.</p>
Datasets for ``Electromagnetic conversion into kinetic and thermal energies''
<pre>This directory contains an index.html file with links to the run directories and idl plotting routines with secondary data for the other figures for the paper "Electromagnetic conversion into kinetic and thermal energies" by A. Brandenburg and N. Protiti. If anything turns out to be incomplete, please email brandenb@nordita.org. </pre>
Data for "Two-stage, low noise quantum frequency conversion of single photons from silicon-vacancy centers in diamond to the telecom C-band"
<p>The silicon-vacancy center in diamond holds great promise as a qubit for quantum communication networks. However, since the optical transitions are located within the visible red spectral region, quantum frequency conversion to low-loss telecommunication wavelengths becomes a necessity for its use in long-range, fiber-linked networks. This work presents a highly efficient, low-noise quantum frequency conversion device for photons emitted by a silicon-vacancy (SiV) center in diamond to the telecom C-band. By using a two-stage difference-frequency mixing scheme SPDC noise is circumvented and Raman noise is minimized, resulting in a very low noise rate of 10.4(7) photons per second as well as an overall device efficiency of 35.6 %. By converting single photons from SiV centers we demonstrate the preservation of photon statistics upon conversion.</p>
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