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zenodo40/100

Source code and simulation results: Efficient rational approximation of optical response functions with the AAA algorithm

<p>This publication provides data published in the article "Efficient rational approximation of optical response functions with the AAA algorithm" [1] in tabulated form along with the Matlab scripts that have been used to produce them. These scripts interface the finite element method solver JCMsuite [2,3]. The article presents rational approximations of optical response functions based on an extended version of the AAA algorithm [4] that allows to efficiently reconstruct sensitivty spectra and gives access to sensitivities of poles, residues, and zeros. Furthermore, the rational approximation of a scalar observalbe is used to construct solutions of the source free Maxwell's equation, i.e., a nonlinear eigenvalue problem.&nbsp;</p> <p><strong>The physical Structure</strong></p> <p>The example is based on the chiral metasurface introduced in [5]. For the sake of simplicity we added infinite layers of SiO\(_2\) to the top and the bottom of the structure. The original structure has a SiO\(_2\) substrate and a layer of PMMA polymethyl methacrylate (PMMA)&nbsp; deposited on top. PMMA can be modelled with the same refractive index of 1.45 as SiO\(_2\). Furthermore, our simulations include the 13 nm indium tin oxide (ITO) coating which drastically reduces the Q-factor as it is slightly absorbing. The accuracy of the discrete model is verified by assessing reflection, transmission, and absorption at 241 evenly spaced points within the specified range. Energy conservation requires that the discrepancy between their sum and the energy entering the system is zero. The numerical discretization is chosen such that the maximum relative error is less than \(3\times10^{&minus;5}\).</p> <p><strong>Dispersion</strong></p> <p>Tabulated data for ITO has been taken from the <a href="https://refractiveindex.info/?shelf=other&amp;book=In2O3-SnO2&amp;page=Konig">refractiveindex.info</a> database (T. A. F. K&ouml;nig et al., 2014, https://doi.org/10.1021/nn501601e) and the data for TiO2 was kindly provided the authors of [5]. The permittivity \(\varepsilon = (n+ik)^2\) is locally approximated as a rational function, i.e., only data in a vicinity of the frequency range of interest is considered. As we aim for a function with the symmetry \(f^\ast(\omega) = f(-\omega^\ast)\) we add the complex conjugated data at negative frequencies and enforce the symmetry in a second step. The partial fraction decomposition of the required function is of the form: \(\varepsilon(\omega) = \varepsilon_\infty + \sum_{j=1}^{4}a_j/(\omega-\omega_j) - a_j^\ast/(\omega+\omega_j^\ast)\) with the residues \(a_j\) and the poles \(\omega_j\). We expect 4 pairs of poles to sufficiently approximate the data within the range of interest (4 with positive and 4 with negative real parts).</p> <h4><strong>Requirements</strong></h4> <ul> <li>JCMsuite (at least 6.2.0)</li> <li>MATLAB (tested with version R2023b)</li> </ul> <p>In order to run the simulations with JCMsuite you must replace corresponding place holders with a path to your installation of JCMsuite. Free trial licenses are available, please refer to the homepage of <a href="https://jcmwave.com/">JCMwave</a>.</p> <p><strong>Usage</strong></p> <p>With the content of 'spectra.zip' you can reproduce results presented in the paper. Running the script 'plots.m' will not start any expensive simulation but use the provided data. With 'dispersion.m' the fits to the material data can be reproduced. Additionally, tabulated data is contained in 'data/ascii'. The archive 'eigenmodes.zip' must be extracted in the same directory as 'spectra.zip'.</p> <p><strong>References</strong></p> <p>[1] Fridtjof Betz, Martin Hammerschmidt, Lin Zschiedrich, Sven Burger, Felix Binkowski: Efficient rational approximation of optical response functions<br>with the AAA algorithm, https://doi.org/10.48550/arXiv.2403.19404.</p> <p>[2] Jan Pomplun, Sven Burger, Lin Zschiedrich, Frank Schmidt,&nbsp;Adaptive finite element method for simulation of optical nano structures, Physica Status Solidi B&nbsp;<strong>244</strong>, 3419 (2007), http://dx.doi.org/10.1002/pssb.200743192.</p> <p>[3] Fridtjof Betz, Felix Binkowski, Sven Burger, RPExpand: Software for Riesz projection expansion of resonance phenomena, SoftwareX <strong>15</strong>, 100763 (2021), https://doi.org/10.1016/j.softx.2021.100763.</p> <p>[4] Y. Nakatsukasa, O. S&egrave;te, and L. N. Trefethen,&nbsp;The AAA Algorithm for Rational Approximation, SIAM Journal on Scientific Computing <strong>40</strong>, A1494 (2018), http://dx.doi.org/10.1137/16M1106122.</p> <p>[5] &nbsp;X. Zhang, Y. Liu, J. Han, Y. Kivshar, and Q. Song, Chiral emission from resonant metasurfaces, Science <strong>377</strong>, 1215 (2022), http://dx.doi.org/%2010.1126/science.abq7870.</p>

opencc-by-4.0Mar 2024View details →
zenodo40/100

FEX3-ECG/Charts01: Least Squares Approximation of ECG Signals with Rational Functions

<p>&nbsp;</p> <p>&nbsp; We introduce a new algorithm for &quot;Least Squares Approximation of ECG Signals with Rational Functions&quot;.&nbsp;Detailed description here: <a href="https://doi.org/10.5281/zenodo.7628747">https://doi.org/10.5281/zenodo.7628747</a> . The following is one result of the approximations and its charts.</p> <p><br> The original ECG signals:<br> &nbsp;&nbsp;&nbsp; DOI:&nbsp;&nbsp;&nbsp;&nbsp; <a href="https://doi.org/10.13026/C28C71">https://doi.org/10.13026/C28C71</a><br> &nbsp;&nbsp;&nbsp; License: Open Data Commons Attribution License v1.0</p> <p>We approached the following signal from the database above:<br> &nbsp;&nbsp; Patient009, the file: S0035_RE.XYZ, vy(Frank lead system)<br> &nbsp;&nbsp; The location of the QRS: 8669th point (8.669 sec)</p> <p>That is:<br> &nbsp; The approximated signal (P QRS T) section: 1:1139, the location of the QRS 371<br> &nbsp; The first signal point = 8299th data point.<br> &nbsp; Detailes:<br> &nbsp;&nbsp;&nbsp; locations of data points :&nbsp; 8299&nbsp; 8300&nbsp; 8301 ..&nbsp;&nbsp;&nbsp; 8669&nbsp;&nbsp; ..&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; 9437<br> &nbsp;&nbsp;&nbsp; indexes of signal points :&nbsp; &nbsp; &nbsp;&nbsp; 1&nbsp;&nbsp; &nbsp; &nbsp;&nbsp; 2 &nbsp;&nbsp; &nbsp;&nbsp;&nbsp; 3&nbsp;&nbsp; ..&nbsp; &nbsp;&nbsp; 371&nbsp;&nbsp; ..&nbsp; &nbsp; &nbsp; &nbsp; 1139<br> &nbsp;&nbsp;&nbsp; values&nbsp; of signal points :&nbsp;&nbsp;&nbsp; 291&nbsp; &nbsp;&nbsp; 282&nbsp;&nbsp; 307&nbsp; ..&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; &nbsp; &nbsp;&nbsp; &nbsp; &nbsp; &nbsp; &nbsp;&nbsp; &nbsp;&nbsp; 352</p> <p>The signal described above is approximated by the following parameters of rational function in the example_1a.m short program.</p> <p><em>The </em><em>grids of charts:</em><br> &nbsp;&nbsp;&nbsp; X axis: 40ms&nbsp; (The sampling rate is 1000Hz)<br> &nbsp;&nbsp;&nbsp; Y axis: 0.1mV (200 A/D units)<br> &nbsp;&nbsp;&nbsp; This is on the original medical ECG paper: 1mm x 1mm.</p> <p>&nbsp;</p> <p><strong>FILES of Charts01.zip:<br> example_1a.m</strong>&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; This file contains a short script of charts.(GNU Octave or MATLAB?)<br> &nbsp;&nbsp;&nbsp;&nbsp; Input: no. <strong><em>The parameters are in this</em></strong><strong><em> short</em></strong><strong><em> program.</em></strong><br> &nbsp;&nbsp;&nbsp;&nbsp; Output: Figure_b_1 and Figure_b_2<br> <strong>PQRST_sgnl_a.m</strong>&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Subroutine (of example_1a.m)</p> <p><strong>Figure_b_1.jpg</strong>&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; First output chart of the example_1a.m<br> &nbsp;&nbsp;&nbsp; blue&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp;&nbsp; &nbsp;&nbsp; An approximation of the P wave<br> &nbsp;&nbsp;&nbsp; red&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; An approximation of the QRS wave<br> &nbsp;&nbsp;&nbsp; yellow&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp;&nbsp; &nbsp;&nbsp; &nbsp; An approximation of the T wave<br> &nbsp;&nbsp;&nbsp; magenta&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; &nbsp; &nbsp; &nbsp; &nbsp;&nbsp; &nbsp; An approximation of the Ta wave</p> <p><strong>Figure_b_2.jpg</strong>&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Second output chart of the example_1a.m<br> &nbsp;&nbsp;&nbsp; blue&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; An approximation of all the waves (the sum of the above)</p> <p><strong>data_a_c.csv</strong>&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Result spreadsheet of the approximation program (decimal comma)<br> <strong>data_a_</strong><strong>p</strong><strong>.csv</strong>&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; &nbsp; Result spreadsheet of the approximation program (decimal point)<br> &nbsp;Columns:<br> &nbsp;&nbsp;&nbsp; R relative&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; &nbsp;&nbsp;&nbsp;&nbsp; &nbsp; &nbsp;&nbsp; QRS relative indexing<br> &nbsp;&nbsp;&nbsp; Original&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; The original ECG signal<br> &nbsp;&nbsp;&nbsp; Approx&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; &nbsp; &nbsp; &nbsp;&nbsp; &nbsp; An approximation of the ECG signal<br> &nbsp;&nbsp;&nbsp; Err220128&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; &nbsp; &nbsp;&nbsp; &nbsp;&nbsp;&nbsp; Error and noise (+date: yymmdd)<br> &nbsp;&nbsp;&nbsp; BL174355&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; &nbsp; &nbsp; &nbsp;&nbsp; &nbsp;&nbsp; Baseline &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;(+time: hhmmss)<br> &nbsp;&nbsp;&nbsp; P(+Ta)&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; &nbsp; &nbsp;&nbsp; &nbsp;&nbsp; &nbsp; &nbsp; An approximation of the P wave (+Ta wave)<br> &nbsp;&nbsp;&nbsp; QRS&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp;&nbsp; &nbsp;&nbsp; An approximation of the QRS wave<br> &nbsp;&nbsp;&nbsp; T&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; &nbsp; &nbsp; &nbsp;&nbsp; &nbsp; &nbsp; &nbsp;&nbsp; &nbsp; An approximation of the T wave<br> &nbsp;&nbsp;&nbsp; V__idy&nbsp; 4&nbsp;&nbsp;&nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp;&nbsp; &nbsp; The length of the ECG vector (normalized, max. = 1mV)</p> <p><strong>image_a_</strong><strong>1</strong><strong>.gif</strong>&nbsp;&nbsp;&nbsp;&nbsp; &nbsp; First&nbsp; chart of the columns in the data_a_?.csv (MS Excel)<br> &nbsp; &nbsp;&nbsp;Original<br> &nbsp; &nbsp;&nbsp;Approx<br> &nbsp; &nbsp;&nbsp;Err220128<br> &nbsp; &nbsp;&nbsp;BL174355</p> <p><strong>image_a_</strong><strong>2</strong><strong>.gif</strong>&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Second chart of the columns in the data_a_?.csv (MS Excel)<br> &nbsp;&nbsp; &nbsp;P(+Ta)<br> &nbsp;&nbsp; &nbsp;QRS<br> &nbsp; &nbsp;&nbsp;T</p> <p>&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp;&nbsp;&nbsp; Kobzos, Laszlo<br> &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp;&nbsp;&nbsp;&nbsp; Location: HU (Budapest)<br> &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; &nbsp; &nbsp; &nbsp;&nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp;&nbsp;&nbsp;&nbsp; email:&nbsp; &nbsp; &nbsp;zehu.kola.ci@gmail.com</p> <p>&nbsp;</p>

opencc-by-4.0Apr 2022View details →
zenodo40/100

FEX3-ECG/Charts02: Least Squares Approximation of ECG Signals with Rational Functions

<p><br> &nbsp; We introduce a new algorithm for &quot;Least Squares Approximation of ECG Signals with Rational Functions&quot;.&nbsp;Detailed description here: <a href="https://doi.org/10.5281/zenodo.7628747">https://doi.org/10.5281/zenodo.7628747</a> .&nbsp;The following figures show the results of some of the approximations.<br> <br> The original ECG signals:<br> &nbsp; DOI:&nbsp;&nbsp;&nbsp;&nbsp; <a href="https://doi.org/10.13026/C28C71">https://doi.org/10.13026/C28C71</a><br> &nbsp; License: Open Data Commons Attribution License v1.0</p> <p><strong><em>Notes:</em></strong></p> <p>- We refer to the database records as follows:&nbsp; s.... = serial number, p... = patient. For example: <strong>s0508_p269</strong>. If we want to specify the location more precisely within the record, we also indicate the lead and the time of the QRS. For example: <strong>s0508_p269, vy, 6689</strong> (Where &quot;vy&quot; is one of the Frank leads.).</p> <p>- The figures were created with Microsoft Excel (gif, non-animated). In addition to the figures, data files of the results are usually also included. In the text files, we used a decimal point (for GNU Octave) or a decimal comma (for Excel). Any text editor can be used to transform them, replacing all commas with points or vice versa.</p> <p>- In some ppaarraamm.txt files, we have written the location and values of the parameters of each approximation (in Hungarian). The starting point of the time coordinate is now the first point of the ECG signal drawing. For the quadratic parameters of the numerator, the values of the two real roots or the conjugate complex root are placed one after the other. Similarly, the quadratic parameters of the denominator have the values of the conjugate complex root one after the other. The data from <strong>example_1a.m </strong>in&nbsp; <a href="https://doi.org/10.5281/zenodo.6479410">https://doi.org/10.5281/zenodo.6479410</a>&nbsp; is from <strong>From_series\s0035_p009\vy\ppaarraamm.txt</strong> also found below.<br> <em>Mini <strong>Hu==&gt;En dictionary</strong>: </em>ha==&gt;if; nincs==&gt;there is none; sz&aacute;ml&aacute;l&oacute;==&gt;numerator; nevező==&gt;denominator; a pontok sz&aacute;ma==&gt;the number of points; nullad- &eacute;s elsőfok&uacute;==&gt;zeroth and first degree; m&aacute;sodfok&uacute;==&gt;second degree; hely_bazis==&gt;location base (the origin of the drawings).</p> <p>- Below, the meaning of the two numbers after the wave letter is related to the number of approximation parameters. For example: P35 means: P wave, 3 is the number of parameters of the numerator (including the main coefficient <strong>d</strong>), while 5 is the number of pole <strong>pairs</strong> (factors) of the denominator. So the number of approximation parameters is 3 + 2&times;5=13.<br> The meaning of Ta here: the approximation includes the Ta wave.</p> <p>- Below is the meaning of the 2&times;6 digit number, for example in filename:&nbsp;<br> &nbsp;&nbsp;&nbsp;&nbsp; <em>yymmdd hhmmss</em>:&nbsp; year month day&nbsp;&nbsp; hour minute second (time stamp).<br> <br> <strong><em>Notes on pole-zero representation:</em></strong></p> <p>- In the figures, the poles are marked with <strong>x</strong> and the zeros with <strong>o</strong>.</p> <p>- In the figures, only one of the two conjugated complex roots was shown, namely always the one falling towards the momentary value of the signal.</p> <p>- The pole of the Ta wave was not marked.</p> <p>- In the<strong> older figures</strong>, only the poles are visible, the zeros are not indicated. When the poles are drawn in the diagram shared with the signs, their location (coordinate <strong>t</strong>) is good, but the imaginary part was taken into account in a different way at that time.</p> <p>- Drawing the imaginary values of the roots on the same diagram as the signs on the <strong>newer figures</strong>, we multiplied them by 50, 100 and 10 for the P, QRS and T waves, respectively.<br> <br> <strong><em>The grids of charts </em></strong>(on the original medical ECG paper: &quot;small squares&quot; = 1mm x 1mm):<br> &nbsp;&nbsp;&nbsp; X axis: 40ms&nbsp; (The sampling rate is 1000Hz)<br> &nbsp;&nbsp;&nbsp; Y axis: 0.1mV (200 A/D units)</p> <p>=====================================================================================</p> <p><strong>Unid-Alte\</strong></p> <p>Diagram of two multipliers.<br> Here, the imaginary part of the poles and zeros is multiplied by 0.3.<br> It can be seen that the pole and zero locations do not coincide with the extremum locations on the alternating direction diagram.<br> <br> <strong>Histogram\</strong></p> <p>All 125 periods of the <strong>s0177_p050</strong> signal were approximated (<strong>vx, vy, vz</strong>). The figure is a histogram of one of the parameters of the T wave of <strong>vz</strong> lead (excluding the 2 extreme values).<br> <br> <strong>s0021_p005-vy\</strong></p> <p>These figures are the steps for approximating a QRS (<strong>s0021_p005, vy, 6810</strong>).<br> <em>Mini <strong>Hu==&gt;En dictionary</strong>:</em> kozelito==&gt;approximate; err......==&gt;discrepancy; kend volt==&gt;this had to be approached</p> <p>rajz-r-y-002---1.gif&nbsp;&nbsp;&nbsp; result of QRS11<br> rajz-r-y-002---2.gif&nbsp;&nbsp;&nbsp; result of QRS12<br> rajz-r-y-002---3.gif&nbsp;&nbsp;&nbsp; result of QRS13<br> &nbsp;&nbsp;&nbsp; The approximation of the small wave on the right side of the QRS is still missing. The approximation below the left side of the QRS is not yet good enough. We entered 2 zeros and multiplied the denominator by a complex conjugate root pairs.<br> rajz-r-y-002---4.gif&nbsp;&nbsp;&nbsp; result of QRS34<br> rajz-r-y-002---5.gif&nbsp;&nbsp;&nbsp; result of QRS35&nbsp; Acceptable.<br> &nbsp;</p> <p>rajz-r-y-002---6.gif&nbsp;&nbsp;&nbsp; after a later approximation, we compared the results of the new QRS77 and QRS35.</p> <p>rajz-y-002-221022_201157_1.gif&nbsp;&nbsp;&nbsp;&nbsp; The final results of this new approximation (indicating the poles and zeros).<br> rajz-y-002-221022_201157_2.gif</p> <p><em>Mini <strong>Hu==&gt;En dictionary</strong></em>: R.hely==&gt;the relative <strong>t</strong> coordinate calculated from the origin; Eredeti==&gt;raw; Approx==&gt;approximate; Err......==&gt;discrepancy, BL......==&gt;baseline<br> <br> <strong>Shapes\</strong></p> <p>Approximation of some important shape types.<br> <em>Mini <strong>Hu==&gt;En dictionary</strong></em>: R.hely==&gt;the relative <strong>t</strong> coordinate calculated from the origin; Eredet==&gt;raw; Approx==&gt;approximate; Err......==&gt;discrepancy, BL......==&gt;baseline; p&oacute;lusok==&gt;poles</p> <p>s0025_p005&nbsp;&nbsp; V3 7009&nbsp;&nbsp; Dome&nbsp;&nbsp; &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;Ta&nbsp; P32&nbsp; T34&nbsp; QRS34<br> s0047_p015&nbsp;&nbsp;&nbsp;&nbsp; II&nbsp; 2758&nbsp;&nbsp; Digitalis&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; P22&nbsp; T33&nbsp; QRS34&nbsp;&nbsp;&nbsp; One pair of poles of QRS and T coincide in the drawing (<strong>t</strong>=32).<br> s0146_p044&nbsp;&nbsp; V4 3725&nbsp;&nbsp; Coronaria T&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Ta&nbsp; P22&nbsp; T22&nbsp; QRS23<br> s0508_p269 aVR 5019&nbsp;&nbsp; Block&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Ta&nbsp; P12&nbsp; T12&nbsp; QRS24<br> s0542_p283&nbsp;&nbsp;&nbsp; vz&nbsp; 2581&nbsp; QRS W-shaped&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; P__&nbsp;&nbsp; T22&nbsp; QRS34&nbsp;&nbsp;&nbsp; There is no P wave in any of the leads. (Atrial fibrillation)<br> <br> <strong>From_series\</strong></p> <p>&nbsp; <em>Mini <strong>Hu==&gt;En dictionary</strong></em>: R.hely==&gt;the relative <strong>t</strong> coordinate calculated from the origin; Eredet==&gt;raw; Approx==&gt;approximate; Err......==&gt;discrepancy, BL......==&gt;baseline; p&oacute;lusok==&gt;poles</p> <table> <tbody> <tr> <td>s.... = S/N, p... = patient:</td> <td>&nbsp; &nbsp; &nbsp; &nbsp;s0001_p119</td> <td>s0002_p196</td> <td>s0034_p163</td> <td>s0035_p009</td> </tr> <tr> <td>&nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp;QRS_location:</td> <td>6938 &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp;10291</td> <td>9067</td> <td>7580</td> <td>8669</td> </tr> <tr> <td><strong>vx</strong></td> <td>Ta&nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp;Ta</td> <td>Ta</td> <td>&nbsp;</td> <td>Ta</td> </tr> <tr> <td>&nbsp;</td> <td>P12&nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp;P12</td> <td>P12</td> <td>P65</td> <td>P13</td> </tr> <tr> <td>&nbsp;</td> <td>T23&nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp;T34</td> <td>T25</td> <td>T35</td> <td>T34</td> </tr> <tr> <td>&nbsp;</td> <td>QRS24&nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; QRS24</td> <td>QRS15</td> <td>QRS89</td> <td>QRS57</td> </tr> <tr> <td><strong>vy</strong></td> <td>Ta</td> <td>&nbsp;</td> <td>Ta</td> <td>Ta</td> </tr> <tr> <td>&nbsp;</td> <td>P24</td> <td>P55</td> <td>P34</td> <td>P13</td> </tr> <tr> <td>&nbsp;</td> <td>T54</td> <td>T24</td> <td>T26</td> <td>T13</td> </tr> <tr> <td>&nbsp;</td> <td>QRS55</td> <td>QRS25</td> <td>QRS47</td> <td>QRS48</td> </tr> <tr> <td><strong>vz</strong></td> <td>&nbsp;</td> <td>&nbsp;</td> <td>Ta</td> <td>Ta</td> </tr> <tr> <td>&nbsp;</td> <td>P65</td> <td>P43</td> <td>P23</td> <td>P11</td> </tr> <tr> <td>&nbsp;</td> <td>T14</td> <td>T33</td> <td>T24</td> <td>T44</td> </tr> <tr> <td>&nbsp;</td> <td>QRS25</td> <td>QRS25</td> <td>QRS27</td> <td>QRS26</td> </tr> </tbody> </table> <p>The s0001_p119\vy\rajz-y-001-190918_210304_vlc.gif image has been expanded with the length of the vector (&quot;V__idy 1&quot;). The origin of the <strong>t</strong> axis (vx, vy, vz) is determined from the curve of the vector length.</p> <p>The figures for <strong>s0001_p119, vx, 10291</strong> are in the s0001_p119_U\vx directory. This is from the same <strong>vx</strong> signal as the previous one (6938), just 4 periods later. There is a U wave in it, T34 was needed instead of T23 to approximate it. The image Rajz-001-005a.gif is in the same directory. On this, we enlarged the part between the T and the next P wave at two periods (Data<strong>1</strong> 6938 and Data<strong>5</strong> 10291) of the vx signal.</p> <p>The figures of <strong>s0002_p196,</strong> <strong>vx, vy, vz, 9067</strong> show that the approximation on the left side of the QRS should be improved, probably by increasing the degree of the denominator.</p> <p>The figures for <strong>s0034_p163, vx, 7580</strong> are in the s0034_p163\vx\ directory. In the figure &quot;rajz-x-003-221031_174534_2.gif&quot; at t=-128, a pole and a zero coincide in the drawing, so we have enlarged this part (around P and QRS) :<br> rajz-x-003-221031_174534_2-zoom.gif.</p> <p>The figures for <strong>s0035_p009, vy, 8669</strong> are in the s0035_p009\vy\ directory. In the figure &quot;rajz-y-004-221031_114914_2.gif&quot; at t=-21, a pole and a zero almost coincide in the drawing.<br> As already written above, the data of example_1a.m (Octave, Matlab) on <a href="https://doi.org/10.5281/zenodo.6479410">https://doi.org/10.5281/zenodo.6479410</a> comes from the file ppaarraamm.txt in the same directory.</p> <p>&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;Kobzos, Laszlo<br> &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Location: HU (Budapest)<br> &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;email:&nbsp;&nbsp; zehu.kola.ci@gmail.com</p>

opencc-by-4.0Nov 2022View details →
geo24/100

Functional Subclone Profiling for Prediction of Treatment-Induced Intratumor Population Shifts and Discovery of Rational Drug Combinations in Human Glioblastoma [SNP]

GEO Series GSE72732. Homo sapiens. 7 samples. Type: Genome variation profiling by SNP array; SNP genotyping by SNP array.

openGEO-OpenDec 2016View details →
geo24/100

Functional Subclone Profiling for Prediction of Treatment-Induced Intratumor Population Shifts and Discovery of Rational Drug Combinations in Human Glioblastoma [expression]

GEO Series GSE72927. Homo sapiens. 24 samples. Type: Expression profiling by array.

openGEO-OpenDec 2016View details →
ClinicalTrials.gov24/100

Patient-specific, Effective, and Rational Functional Connectivity Targeting for DBS in OCD

ClinicalTrials.gov study NCT03244852. IPD Sharing: NO. Countries: 1. Publications: 0.

closedIPD-NOFeb 2026View details →

ScienceDex guides

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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.

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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.

allen-brain-atlas
neuroscienceopenDocumentation, web resources, and API references are available online.
Last verified 2026-04-30Open record

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.

abode-home-cage
behavioral-neuroscienceopenThe DataShare record exposes download links for annotations, documentation, license text, and the zipped per-snippet data directory.
Last verified 2026-04-30Open record

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.

dandi-nwb
electrophysiologyopenPublished Dandiset metadata and archive endpoints are available through the production DANDI API.
Last verified 2026-04-30Open record

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.

ibl
behavioral-neuroscienceopenPublic sessions can be searched and loaded from the IBL public data server through ONE.
Last verified 2026-04-29Open record

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.

openneuro
neuroscienceopenPublished datasets are available on demand over the internet.
Last verified 2026-04-29Open record