cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.4231/r7r20zb7
title: 32-digit values of the first 100 recurrence coefficients for symmetric subrange Jacobi polynomials

description: &lt;p&gt;32-digit values of the first 100 recurrence coefficients for orthogonal polynomials relative to the weight function w(x)=(1-x)^a*(1+x)^b on [-c,c], c=1/2, a=-1/2, b=1/2, are computed by a 1-component discretization procedure using the routine sr_symm_subrange_jacobi(32,100) with (global) input parameters dig=34, c=1/2, a=-1/2, b=1/2. For details concerning the discretization, see Section 2 in Walter Gautschi, &quot;Sub-range Jacobi polynomials&quot;, Numerical algorithms 61 (2012), 649-657. doi: s11075-012-9556-z. The software provided in this dataset allows generating an arbitrary number N of recurrence coefficients for arbitrary parameters 0 &lt; c &lt; 1, a &gt; -1, b &gt; -1 and for different precisions.&lt;/p&gt;
description: 32-digit values of the first 100 recurrence coefficients for the weight function w(x)=(1-x)^a*(1+x)^b on [-c,c], c=1/2, a=-1/2, b=1/2
DOI: 10.4231/r7cr5rb4
title: Purdue University Buildings Demolition, Construction Images, October 2016, MATH Building Camera

description: &lt;p&gt;[[Video(http://www.youtube.com/watch?v=NzHVPihbi4A)]]&lt;/p&gt;

&lt;p&gt;Purdue&#39;s campus landscape continues to change with the construction of new buildings and the remodel of old buildings. In 2012 the Engineering Administration Building (ENAD) and the iconic Heat and Power Plant-North (HPN) were targeted for demolition to make way for the construction of the Wilmeth Active Learning Center (WALC); a building with offices, collaborative spaces and classrooms with an emphasis on new instructional models. The Purdue University Lyles School of Civil Engineering capitalized on a key opportunity for education and research. Five cameras were installed to capture images from the demolition of the Engineering Administration Building and the Power Plant, to the construction of the Wilmeth Active Learning Center. The images from 3 fixed cameras situated on the Mathematical Sciences Building (MATH) and the Potter (A. A.) Engineering Center (POTR) can be accessed and used for educational and research purposes.&lt;/p&gt;

&lt;p&gt;Representative time lapse videos were created from these three cameras for each month of the project. The time lapse videos created from these images - 08:00 to 18:00, 7 days a week in each month - are accessible here: &lt;a href="http://dx.doi.org/10.4231/R70P0WXD"&gt;http://dx.doi.org/10.4231/R70P0WXD&lt;/a&gt;.&lt;/p&gt;
description: Two iconic buildings on the Purdue University campus, the Engineering Administration Building and the retired Heating and Power Plant-North, were targeted for demolition in 2012 to make way for the construction of the Wilmeth Active Learning Center.
DOI: 10.4231/r7833q00
title: Purdue University Buildings Demolition, Construction Images, October 2016, POTR Building Camera 2

description: &lt;p&gt;[[Video(http://www.youtube.com/watch?v=Im3WzByGU4g)]]&lt;/p&gt;
&lt;p&gt;Purdue&#39;s campus landscape continues to change with the construction of new buildings and the remodel of old buildings. In 2012 the Engineering Administration Building (ENAD) and the iconic Heat and Power Plant-North (HPN) were targeted for demolition to make way for the construction of the Wilmeth Active Learning Center (WALC); a building with offices, collaborative spaces and classrooms with an emphasis on new instructional models. The Purdue University Lyles School of Civil Engineering capitalized on a key opportunity for education and research. Five cameras were installed to capture images from the demolition of the Engineering Administration Building and the Power Plant, to the construction of the Wilmeth Active Learning Center. The images from 3 fixed cameras situated on the Mathematical Sciences Building (MATH) and the Potter (A. A.) Engineering Center (POTR) can be accessed and used for educational and research purposes.&lt;/p&gt;

&lt;p&gt;Representative time lapse videos were created from these three cameras for each month of the project. The time lapse videos created from these images - 08:00 to 18:00, 7 days a week in each month - are accessible here: &lt;a href="http://dx.doi.org/10.4231/R70P0WXD"&gt;http://dx.doi.org/10.4231/R70P0WXD&lt;/a&gt;.&lt;/p&gt;
description: Two iconic buildings on the Purdue University campus, the Engineering Administration Building and the retired Heating and Power Plant-North, were targeted for demolition in 2012 to make way for the construction of the Wilmeth Active Learning Center.
DOI: 10.4231/r7m906mw
title: 32-digit values of the first 100 recurrence coefficients for lower subrange Jacobi polynomials

description: &lt;p&gt;32-digit values of the first 100 recurrence coefficients for orthogonal polynomials relative to the weight function w(x)=(1-x)^a*(1+x)^b on [-1,c], c=0, a=-1/2, b=1/2, are computed by a 2-component discretization procedure using the routine sr_lower_subrange_jacobi(32,100) with (global) input parameters dig=34, c=0, a=-1/2, b=1/2. For details concerning the discretization, see Section 2 in Walter Gautschi, &quot;Sub-range Jacobi polynomials&quot;, Numerical algorithms 61 (2012), 649-657. doi: 10.1007/s11075-012-9556-z. The software provided in this dataset allows generating an arbitrary number N of recurrence coefficients for arbitrary parameters -1 &lt; c &lt; 1, a &gt; -1, b &gt; -1 and for different precisions.&lt;/p&gt;
description: 32-digit values of the first 100 recurrence coefficients for the weight function w(x ) = (1-x)^a*(1+x)^b on [-1,c], c = 0, a = -1/2, b = 1/2
DOI: 10.4231/r7vt1q2n
title: 32-digit values of the first 100 recurrence coefficients for upper subrange Jacobi polynomials

description: &lt;p&gt;32-digit values of the first 100 recurrence coefficients for orthogonal polynomials relative to the weight function w(x)=(1-x)^a*(1+x)^b on [c,1], c=0, a=-1/2, b=1/2, are computed by a 2-component discretization procedure using the routine sr_upper_subrange_jacobi(32,100) with (global) input parameters dig=34, c=0, a=-1/2, b=1/2. The procedure is analogous to the one for lower subrange Jacobi polynomials, described in Section 2 of Walter Gautschi, &quot;Sub-range Jacobi polynomials&quot;, Numerical algorithms 61 (2012), 649-657. doi: 10.1007/s11075-012-9556-z. The software provided in this dataset allows generating an arbitrary number N of recurrence coefficients for arbitrary parameters -1 &lt; c &lt; 1, a &gt; - 1, b &gt; -1 and for different precisions.&lt;/p&gt;
description: 32-digit values of the first 100 recurrence coefficients for the weight function w(x)=(1-x)^a*(1+x)^b on [c,1], c=0, a=-1/2, b=1/2
DOI: 10.4231/r7gh9fx2
title: 32-digit values of the first 100 recurrence coefficients for symmetric subrange generalized Hermite polynomials

description: &lt;p&gt;32-digit values of the first 100 recurrence coefficients for orthogonal polynomials relative to the weight function w(x)=x^(2*mu)*exp(-x^2) on [-c,c], c = 1, mu=0, are computed by a moment-based method using the routine sr_symm_subrange_ghermite(dig,32,100,1,0), where dig=108 has been determined by the routine dig_symm_subrange_ghermite(100,1,0,100,4,32). The software provided in this dataset allows generating an arbitrary number N of recurrence coefficients for arbitrary c &gt; 0, mu&gt;-1/2, as well as for different precisions. The polynomials so obtained are closely related to what in quantum chemistry and quantum physics are known as Rys polynomials orthogonal on [-1,1] with respect to the weight function w(x)=exp(-c*x^2); cf. Table 2.2 in Bernard Shizgal, &quot;Spectral methods in chemistry and physics: applications to kinetic theory and quantum mechanics&quot;, Scientific Computation, Springer, Dordrecht, 2015. Indeed, all alpha-coefficients of the (monic) Rys polynomials are those obtained here divided by c; the same holds for the first beta-coefficient, whereas the remaining beta-coefficients are those obtained here divided by c&lt;sup class="moz-txt-sup"&gt;&lt;span style="display:inline-block;width:0;height:0;overflow:hidden"&gt;^&lt;/span&gt;2&lt;/sup&gt;.&lt;/p&gt;
description: 32-digit values of the first 100 recurrence coefficients for the weight function w(x)=x^(2*mu)*exp(-x^2) on [-c,c], c=1, mu=0
DOI: 10.4231/r79w0cg7
title: MEIGS Soil Ecology Project - Turco Lab 2014-2015

description: &lt;p&gt;Gas samples and soil data were taken from two adjacent sites. One site used conventional farming methods and the other used organic methods to grow crops. These sites were managed by the lab of Lori Hoagland of Purdue University. Each site contained 3 plots each with one replicant of soybeans and tomatoes. Gas samples were collected into vacuum evacuated vials every 15 minutes for a total of 60 minutes and 5 samples per replicant at each sample location. Gas samples were taken roughly every week from April 19&lt;sup&gt;th&lt;/sup&gt; to November 8&lt;sup&gt;th&lt;/sup&gt; in 2014 and June 11&lt;sup&gt;th&lt;/sup&gt; to September 21&lt;sup&gt;st&lt;/sup&gt; in 2015.&lt;/p&gt;

&lt;p&gt;Gases were measured using food pans modified for the purpose.&lt;sup&gt;1&lt;/sup&gt; Samples were run immediately upon return to the laboratory for analysis by gas chromatography (GC) using an Agilent 7890 GC equipped with a FID detector, a TCD detector and a micro ECD (Santa Clara, CA) .  A PAL model 120 autosampler upgraded for headspace analysis (Quantum Analytics, Foster City, CA) was used to inject samples using 20 mL vials with magnetic caps (Agilent, Santa Clara, CA catalog # 5188-2759).  The GC was further customized (Custom Solutions Group, Katy, TX) by the installation of two pneumatically actuated 10 port gas sampling and backflush-to-vent valves, and a 6 port series-bypass valve on Valcon E rotors, and a switching solenoid valve for purge of valve loops between injections.   Four columns were installed; a HayeSep N 80/10 mesh micro-pack stainless steel, a HayeSepQ 80/100 mesh micropack stainless steel column, a HayeSep N 80/100 mesh silcosteel and a HayeSepQ 80/100 mesh micropack silcosteel, all with the dimensions of 4&rsquo; x 1/16&rdquo;.   Helium was used as a carrier gas and make-up gas except for the ECD which used nitrogen as make-up gas.  Injector temperature was 100&deg; C and flow rate was set at 40 mL min&lt;sup&gt;-1&lt;/sup&gt;.&lt;/p&gt;

&lt;p&gt;Soil temperature and moisture were measured using Spectrum Technologies model 1650 dataloggers. Data was taken from 3 WaterScout SM 100 soil moisture sensors and one soil temperature sensors. Separate data loggers measured the soil moisture and temperature at east and west locations at each site (organic and conventional). Gas and datalogger data was taken from April to November in 2014 and June to September in 2015.&lt;/p&gt;
description: The purpose of this project was to study the effects of organic and conventional farming methods on soil microbial ecosystems by monitoring greenhouse gas (GHG) emissions from the soil during the planting season.
DOI: 10.4231/r7736nwn
title: 32-digit values of the first 100 recurrence coefficients for upper subrange generalized Hermite polynomials

description: &lt;p&gt;32-digit values of the first 100 recurrence coefficients for orthogonal polynomials relative to the weight function w(x)=x^(2*mu)*exp(-x&lt;sup class="moz-txt-sup"&gt;&lt;span style="display:inline-block;width:0;height:0;overflow:hidden"&gt;^&lt;/span&gt;2&lt;/sup&gt;) on [c,Inf], c=1, mu=0, are computed by a moment-based method using the routine sr_upper_subrange_ghermite(dig,32,100,1,0), where dig=156 has been determined by the routine dig_upper_subrange_ghermite(100,1,0,148,4,32). The software provided in this dataset allows generating an arbitrary number N of recurrence coefficients for arbitrary c &gt; 0, mu &gt; -1/2, as well as for different precisions.&lt;/p&gt;
description: 32-digit values of the first 100 recurrence coefficients for the weight function w(x)=x^(2*mu)*exp(-x^2) on [c,Inf], c=1, mu=0
DOI: 10.4231/r73b5x4w
title: 32-digit values of the first 100 recurrence coefficients for symmetric subrange generalized Hermite polynomials with exponent -1/2

description: &lt;p&gt;32-digit values of the first 100 recurrence coefficients for orthogonal polynomials relative to the weight function w(x)=x^(2*mu)*exp(-x&lt;sup class="moz-txt-sup"&gt;&lt;span style="display:inline-block;width:0;height:0;overflow:hidden"&gt;^&lt;/span&gt;2&lt;/sup&gt;) on [-c,c], c=1, mu=-1/4, are computed by a moment-based method using the routine sr_symm_subrange_ghermite(dig,32,100,1,-1/4), where dig=108 has been determined by the routine dig_symm_subrange_ghermite (100,1,-1/4,100,4,32). The software provided in this dataset allows generating an arbitrary number N of recurrence coefficients for arbitrary c &gt; 0, mu &gt; -1/2, as well as for different precisions.&lt;/p&gt;
description: 32-digit values of the first 100 recurrence coefficients for the weight function w(x)=x^(2*mu)*exp(-x^2) on [-c,c], c=1, mu=-1/4
DOI: 10.4231/r7bv7dkm
title: 32-digit values of the first 100 recurrence coefficients for lower subrange generalized Hermite polynomials

description: &lt;p&gt;32-digit values of the first 100 recurrence coefficients for orthogonal polynomials relative to the weight function w(x)=x^(2*mu)*exp(-x^2) on [0,c], c=1, mu=0, are computed by a moment-based method using the routine sr_lower_subrange_ghermite(dig,32,100,1,0), where dig=184 has been determined by the routine dig_lower_subrange_ghermite(100,1,0,176,4,32). The software provided in this dataset allows generating an arbitrary number N of recurrence coefficients for arbitrary c&gt;0, mu&gt;-1/2, as well as for different precisions. The polynomials so obtained are closely related to what in quantum chemistry and quantum physics are known as Rys polynomials orhogonal on [-1,1] with respect to the weight function w(x)=exp(-c*x^2); cf. Table 2.2 in Bernard Shizgal, &quot;Spectral methods in chemistry and physics: applications to kinetic theory and quantum mechanics&quot;, Scientific Computation, Springer, Dordrecht, 2015. Indeed, all alpha-coefficients of the (monic) Rys polynomials are those obtained here divided by c; the same holds for the first beta-coefficient, whereas the remaining beta-coefficients are those obtained here divided by c^2.&lt;/p&gt;
description: 32-digit values of the first 100 recurrence coefficients for the weight function w(x)=x^(2*mu)*exp(-x^2) on [0,c], c=1, mu=0
DOI: 10.4231/r7zk5dnk
title: 32-digit values of the first 100 recurrence coefficients for symmetric subrange generalized Hermite polynomials with exponent 1/2

description: &lt;p&gt;32-digit values of the first 100 recurrence coefficients for orthogonal polynomials relative to the weight function w(x)=x^(2*mu)*exp(-x^2) on [-c,c], c=1, mu=1/4, are computed by a moment-based method using the routine sr_symm_subrange_ghermite(dig,32,100,1,1/4), where dig=108 has been determined by the routine dig_symm_subrange_ghermite (100,1,1/4,100,4,32). The software provided in this dataset allows generating an arbitrary number N of recurrence coefficients for arbitrary c &gt; 0, mu &gt; -1/2, as well as for different precisions.&lt;/p&gt;
description: 32-digit values of the first 100 recurrence coefficients for the weight function w(x)=x^(2*mu)*exp(-x^2) on [-c,c], c=1, mu=1/4
DOI: 10.4231/r7q23x6v
title: 32-digit values of the first 100 recurrence coefficients for lower subrange generalized Hermite polynomials with exponent -1/2

description: &lt;p&gt;32-digit values of the first 100 recurrence coefficients for orthogonal polynomials relative to the weight function w(x)=x^(2*mu)*exp(-x&lt;sup class="moz-txt-sup"&gt;&lt;span style="display:inline-block;width:0;height:0;overflow:hidden"&gt;^&lt;/span&gt;2&lt;/sup&gt;) on [0,c], c=1, mu=-1/4, are computed by a moment-based method using the routine sr_lower_subrange_ghermite(dig,32,100,1,-1/4), where dig=184 has been determined by the routine dig_lower_subrange_ghermite (100,1,-1/4,176,4,32). The software provided in this dataset allows generating an arbitrary number N of recurrence coefficients for arbitrary c &gt; 0, mu &gt; -1/2, as well as for different precisions.&lt;/p&gt;
description: 32-digit values of the first 100 recurrence coefficients for the weight function w(x)=x^(2*mu)*exp(-x^2) on [0,c], c=1, mu=-1/4
DOI: 10.4231/r7tt4nxv
title: 32-digit values of the first 100 recurrence coefficients for lower subrange generalized Hermite polynomials with exponent 1/2

description: &lt;p&gt;32-digit values of the first 100 recurrence coefficients for orthogonal polynomials relative to the weight function w(x)=x^(2*mu)*exp(-x&lt;sup class="moz-txt-sup"&gt;&lt;span style="display:inline-block;width:0;height:0;overflow:hidden"&gt;^&lt;/span&gt;2&lt;/sup&gt;) on [0,c], c=1, mu=1/4, are computed by a moment-based method using the routine sr_lower_subrange_ghermite(dig,32,100,1,1/4), where dig=184 has been determined by the routine dig_lower_subrange_ghermite (100,1,1/4,176,4,32). The software provided in this dataset allows generating an arbitrary number N of recurrence coefficients for arbitrary c &gt; 0, mu &gt; -1/2, as well as for different precisions.&lt;/p&gt;
description: 32-digit values of the first 100 recurrence coefficients for the weight function w(x)=x^(2*mu)*exp(-x^2) on [0,c], c=1, mu=1/4
DOI: 10.4231/r7fn145h
title: 32-digit values of the first 100 recurrence coefficients for upper subrange generalized Hermite polynomials with exponent -1/2

description: &lt;p&gt;32-digit values of the first 100 recurrence coefficients for orthogonal polynomials relative to the weight function w(x)=x^(2*mu)*exp(-x&lt;sup class="moz-txt-sup"&gt;&lt;span style="display:inline-block;width:0;height:0;overflow:hidden"&gt;^&lt;/span&gt;2&lt;/sup&gt;) on [c,Inf], c=1, mu=-1/4, are computed by a moment-based method using the routine sr_upper_subrange_ghermite(dig,32,100,1,-1/4), where dig=152 has been determined by the routine dig_upper_subrange_ghermite(100,1,-1/4,144,4,32). The software provided in this dataset allows generating an arbitrary number N of recurrence coefficients for arbitrary c &gt; 0, mu &gt; -1/2, as well as for different precisions.&lt;/p&gt;
description: 32-digit values of the first 100 recurrence coefficients for the weight function w(x)=x^(2*mu)*exp(-x^2) on [c,Inf], c=1, mu=-1/4
DOI: 10.15468/dl.z5bcxc
title: Occurrence Download

description: A dataset containing 35 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "TaxonKey is Megapodius pritchardii"
 ]
}

 The dataset includes 35 records from 7 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0059342-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.4231/r7k935hz
title: 32-digit values of the first 100 recurrence coefficients for upper subrange generalized Hermite polynomials with exponent 1/2

description: &lt;p&gt;32-digit values of the first 100 recurrence coefficients for orthogonal polynomials relative to the weight function w(x)=x^(2*mu)*exp(-x&lt;sup class="moz-txt-sup"&gt;&lt;span style="display:inline-block;width:0;height:0;overflow:hidden"&gt;^&lt;/span&gt;2&lt;/sup&gt;) on [c,Inf], c=1, mu=1/4, are computed by a moment-based method using the routine sr_upper_subrange_ghermite(dig,32,100,1,1/4), where dig=152 has been determined by the routine dig_upper_subrange_ghermite(100,1,1/4,144,4,32). The software provided in this dataset allows generating an arbitrary number N of recurrence coefficients for arbitrary c &gt; 0, mu &gt; -1/4, as well as for different precisions.&lt;/p&gt;
description: 32-digit values of the first 100 recurrence coefficients for the weight function w(x)=x^(2*mu)*exp(-x^2) on [c,Inf], c=1, mu=1/4
DOI: 10.4231/r7639mqt
title: 32-digit values of the first 100 recurrence coefficients for the weight function w(x)=log(1/x) on [0,1]

description: &lt;p&gt;32-digit values of the first 100 recurrence coefficients for orthogonal polynomials relative to the weight function w(x)=x^a* [log(1/x)]^b on [0,1], a=0, b=1, are computed by a moment-based method using the routine sr_l_alglog(dig,32,100,0,1), where dig=176 has been determined by the routine dig_l_alglog(100,0,1,168,4,32). The results are in agreement, except for occasional endfigure errors of 1 unit, with the first 20 recurrence coefficients given to 12 digits in Table 1 of Bernard Danloy, &quot;Numerical construction of Gaussian quadrature formulas for int_0^1 (-Log x)*x^a*f(x)dx and int_0^Inf E_m(x)f(x)dx, Math. Comp. 27 (1973), 861-869. Use of the routine sgauss.m in the dataset doi:10.4231/R72805KQ also verified to the same accuracy the 10- and 20-point Gaussian quadrature formulae given in Table 2 of this reference.The software provided in this dataset allows generating an arbitrary number N of recurrence coefficients for arbitrary a &gt; -1, b &gt; -1, as well as for different precisions. If the singularities, with the same exponents, occur at the right endpoint, that is, if w(x)=(1-x)^a*[log(1/(1-x))]^b on [0,1], then the alpha-coefficients must be replaced by 1 minus the present ones, whereas the beta-coefficients remain the same.&lt;/p&gt;
description: 32-digit values of the first 100 recurrence coefficients for the weight function w(x)=x^a*[log(1/x)]^b on [0,1], a = 0, b = 1
DOI: 10.4231/r78w3b9d
title: Bridge Approach Construction Time-Lapse

description: &lt;p&gt;[[Video(http://www.youtube.com/watch?v=YtZ3887IoX4)]]&lt;/p&gt;

&lt;p&gt;The construction of the bridge shown in this video is part of a $350,000,000 project that upgrades and grade-separates 13 miles of US 31 between I-465 and Indiana State Road 38. The upgraded 13-mile stretch features 11 new interchanges and eliminates 32 traffic signals. This video shows the concrete bridge deck approach construction.&lt;/p&gt;

&lt;p&gt;This project is located at &lt;a href="https://www.google.com/maps/@40.0419461,-86.1356969,423a,20y,2.8t/data=!3m1!1e3"&gt;40.0419461, -86.1356969&lt;/a&gt;.&lt;/p&gt;
description: This video documents the construction of the northbound bridge approach of US 31 over 191st Street in Westfield, Indiana.
DOI: 10.4231/r72b8w0h
title: 32-digit values of the first 100 recurrence coefficients for the weight function w(x)=[log(1/x)]^2 on [0,1]

description: &lt;p&gt;32-digit values of the first 100 recurrence coefficients for orthogonal polynomials relative to the weight function w(x)=x^a*[log(1/x)]^b on [0,1], a=0, b=2, are computed by a moment-based method using the routine sr_l_alglog(dig,32,100,0,2), where dig=176 has been determined by the routine dig_l_alglog(100,0,2,168,4,32). The software provided in this dataset allows generating an arbitrary number N of recurrence coefficients for arbitrary a &gt; -1, b &gt; -1, as well as for different precisions. If the singularities, with the same exponents, occur at the right endpoint, that is, if w(x)=(1-x)^a*[log(1/(1-x))]^b on [0,1], then the alpha-coefficients must be replaced by 1 minus the present ones, whereas the beta-coefficients remain the same.&lt;/p&gt;
description: 32-digit values of the first 100 recurrence coefficients for the weight function w(x)=x^a*[log(1/x)]^b on [0,1], a=0, b=2
DOI: 10.4231/r7xk8ch6
title: 32-digit values of the first 100 recurrence coefficients for the weight function w(x)=x^(-1/2)*[log(1/x)]^3 on [0,1]

description: &lt;p&gt;32-digit values of the first 100 recurrence coefficients for orthogonal polynomials relative to the weight function w(x)=x^a*[log(1/x)]^b on [0,1], a=-1/2, b=3, are computed by a moment-based method using the routine sr_l_alglog(dig,32,100,-1/2,3), where dig=172 has been determined by the routine dig_l_alglog(100,-1/2,3,164,4,32). The software provided in this dataset allows generating an arbitrary number N of recurrence coefficients for arbitrary a &gt; -1, b &gt; -1, as well as for different precisions. If the singularities, with the same exponents, occur at the right endpoint, that is, if w(x)=(1-x)^a*[log(1/(1-x))]^b, then the alpha-coefficients must be replaced by 1 minus the present ones, whereas the beta-coefficients remain the same.&lt;/p&gt;
description: 32-digit values of the first 100 recurrence coefficients for the weight function w(x)=x^a*[log(1/x)]^b on [0,1], a=-1/2, b=3