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Dataset and Software for The Relationships Between Large-scale Variations in Shear Velocity, Density, and Compressional Velocity in the Earth's Mantle
<p><strong>Is there a chemically distinct reservoir in the Earth?</strong><br><strong>Do superplumes overly denser-than-average material?</strong><br><strong>Can we detect these anomalies with seismic data?</strong><br><strong>Can we evaluate statistical significance of the features in tomography?</strong></p><p>This study presents the <strong>strongest evidence</strong> to date (ca. 2015) of <strong>large-scale thermo-chemical heterogeneities in the lowermost mantle</strong> using the full spectrum of seismic data. A large data set of surface-wave phase anomalies, body-wave travel times, normal-mode splitting functions and long-period waveforms is used to investigate the scaling between shear velocity, density and compressional velocity in the Earth's mantle (ϱ=dln ρ/dln vS, ν=dln vS/dln vP). Our preferred joint model consists of denser-than-average anomalies (∼1% peak-to-peak) at the base of the mantle roughly coincident with the low-velocity superplumes. The relative variation of shear velocity, density and compressional velocity in our study disfavors a purely thermal contribution to heterogeneity in the lowermost mantle, with implications for the long-term stability and evolution of superplumes.</p><p><strong>Note on Odd Degree Structure:</strong></p><p>Since the self-coupled normal-mode splitting observations constrain only even-degree density variations, all inversions strongly disfavored even-degree vS-ρ correlation (R2 ~ –0.46 to –0.25) in the lowermost mantle, which also disfavors a purely thermal contribution to heterogeneity in this region. However, the starting assumptions on positive vS-ρ correlation persisted in the remaining regions and for odd degree variations. In viscosity inversions with the geoid, opposing sign of the correlation of the longest wavelength even-versus odd-degree structure maps into a region of reduced viscosity in the lower mantle (Rudolph et al., 2020, doi:10.1029/2020gc009335). While important for such dynamical implications, <strong>odd-degree density variations in the lowermost mantle are poorly constrained in this study and should not be interpreted</strong>. We therefore used even-degree variations up to degree 6 for our inferences on thermo-chemical variations in the lowermost mantle (Figure 14), and provide those values in the files below.</p><p><strong>Feedback/Questions?</strong> Please contact Raj Moulik (<a href="https://rajmoulik.com">rajmoulik.com</a>) at <a href="mailto:moulik@caa.columbia.edu?subject=Query%20from%20Zenodo">moulik@caa.columbia.edu</a> </p><p><strong>Reference:</strong></p><p><i>Please cite the following work if you use this data or software.</i></p><ul><li>Moulik, P. & Ekström, G., 2016. The relationships between large-scale variations in shear velocity, density and compressional velocity in the Earth's mantle, <i>J. Geophys. Res.</i>, <strong>121</strong>, doi: <a href="http://dx.doi.org/10.1002/2015JB012679">10.1002/2015JB012679</a>. <a href="https://rajmoulik.com/Publications/MoulikEkstrom_JGR2016.pdf"><i>pdf</i></a></li></ul><p><i>You can also cite the dataset and software from this Zenodo page (Optional).</i></p><p>Moulik, P. & Ekström, G. (2016). Dataset and Software for The Relationships Between Large-scale Variations in Shear Velocity, Density, and Compressional Velocity in the Earth's Mantle. In J. Geophys. Res. Solid Earth (v1.0, Vol. 121, pp. 2737–2771). Zenodo. doi: <a href="https://doi.org/10.5281/zenodo.8356540">10.5281/zenodo.8356540</a></p><p><strong>Data Products:</strong></p><ul><li><strong>ME16_Figures(</strong><a href="https://zenodo.org/api/files/9aa99409-20ae-495e-b5a3-288fd57ecaeb/ME16_Figures.tar.gz"><strong>.tar.gz</strong></a><strong> or </strong><a href="https://zenodo.org/api/files/9aa99409-20ae-495e-b5a3-288fd57ecaeb/ME16_Figures.pdf"><strong>.pdf</strong></a><strong>)</strong> - contains all figures from the paper in .png format</li><li><a href="https://zenodo.org/api/files/9aa99409-20ae-495e-b5a3-288fd57ecaeb/ME16"><strong>ME16</strong></a><strong> - </strong>Coefficients of the spline basis functions for each parameter. Refer cij in equation 3. This is our preferred global model of anisotropic elastic parameters and density. Density variations are allowed to deviate from a constant scaling with shear-velocity variations in the lowermost mantle, which is required to fit the longest-period normal modes (e.g. 0S2). Radial anisotropy is confined to the uppermost mantle (that is, since the anisotropy is parameterized with only the four uppermost splines, it becomes very small below a depth of 250 km, and vanishes at 410 km). This is an updated version of S362ANI+M (Moulik and Ekström, 2014) which did not solve independently for density and compressional-wave velocity variations and imposed a constant scaling throughout the mantle instead (ϱ=0, ν=1/0.55).</li><li><a href="https://zenodo.org/api/files/9aa99409-20ae-495e-b5a3-288fd57ecaeb/STW105"><strong>STW105</strong></a> - reference model used in ME16. Described in Kustowski et al. (2008)</li><li><a href="https://zenodo.org/api/files/9aa99409-20ae-495e-b5a3-288fd57ecaeb/setup.cfg"><strong>setup.cfg</strong></a><strong> - </strong>Some configuration metadata relevant to this model for reproducibility.</li><li><a href="https://zenodo.org/api/files/9aa99409-20ae-495e-b5a3-288fd57ecaeb/epix.tar.gz"><strong>epix.tar.gz</strong></a> - Perturbations in horizontally (<i>vsh</i>) and vertically polarized shear velocity (<i>vsv</i>), Voigt-average isotropic shear-wave (<i>vs</i>) and compressional-wave velocity (<i>vp</i>), density (<i>rho</i>). anisotropy (<i>as</i>) and topography of the internal boundaries. This is calculated from the spline coefficients at every 1 by 1 degree cell-centered pixel and at every ~25 km depth region from Moho to the core-mantle boundary and stored in extended pixel format (.epix) ASCII files. Even-degree variations up to degree 6 are provided for density (<i>rho_even6)</i> and isotropic shear-wave velocity (<i>vs_even6</i>), which should be used for density inferences on thermochemical structure (See note above).</li><li><a href="https://zenodo.org/api/files/9aa99409-20ae-495e-b5a3-288fd57ecaeb/ME16.BOX25km_PIX1X1.avni.nc4"><strong>ME16.BOX25km_PIX1X1.avni.nc4</strong></a> - The perturbations in a standard AVNI format that utilizes the NETCDF4 container format. This file can be read in Python using either xarray or AVNI libraries. For example, to plot even-degree variations up to degree 6 in Voigt-averaged shear velocity perturbations at the bottom of the mantle (2875-2891 km depth)<ul><li><i>import xarray as xr</i></li><li><i>ds = xr.open_dataset('ME16.BOX25km_PIX1X1.avni.nc4')</i></li><li><i>ds['vs_even6'][-1].plot()</i></li></ul></li><li><a href="https://zenodo.org/api/files/9aa99409-20ae-495e-b5a3-288fd57ecaeb/PROGRAMS.tar.gz"><strong>PROGRAMS.tar.gz</strong></a> - Fortran tools for obtaining model values at specific locations. After creating the executables from source code in the <i>src</i> folder, the <i>readme</i> script generates most of the epix files provided in epix.tar.gz above<strong>.</strong></li><li><a href="https://zenodo.org/api/files/9aa99409-20ae-495e-b5a3-288fd57ecaeb/profilescaling.txt"><strong>profilescaling.txt</strong></a> - contains the median scaling ratios as used in Figure 15(a).</li><li><a href="https://zenodo.org/api/files/9aa99409-20ae-495e-b5a3-288fd57ecaeb/scaling3D_MoulikJGR16.tar.gz"><strong>scaling3D_MoulikJGR16.tar.gz</strong></a> - contains the scaling ratios and poisson ratio calculated from the joint model, as used in Figure 15(b).</li></ul>
Software Plagiarism Detection on Intermediate Representation Data Set
<p>This data set contains the necessary files used for the bachelor's thesis Software Plagiarism Detection on Intermediate Representation.</p> <p>This includes the data sets for the tests, the implemented code and scripts for the evaluation as well as referenced work.</p> <p> </p>
Simulation data and software scripts used in calculus of ∆36 signature from EMAC clumped O2 isotope-inclusive model
<p>This publication contains simulation data and software scripts for calculating quantities related to clumped oxygen isotope signature (∆<sub>36</sub>) derivation, as described in the "static" framework of Yeung‍ et‍ al. (2016), hereinafter "Y16") and subsequently used in Yeung‍ et‍ al.‍ (2019) analysis. We provide the output of the 1950–2011 transient simulation with EMAC model with explicit "dynamic" simulation of ∆<sub>36</sub> (i.e. <sup>18</sup>O<sup>18</sup>O isotopologues undergoing transport, mixing and O(<sup>3</sup>P)-mediated isotope equilibration) to demonstrate the importance of several assumptions/simplifications involved in the static calculus.</p> <p> </p> <p>Please refer to .README.pdf for details.</p>
Cataloging Dependency Injection Anti-Patterns in Software Systems
<p><strong>Background</strong> Dependency Injection (DI) is a commonly applied mechanism to decouple classes from their dependencies in order to provide better modularization of software. In the context of Java, the availability of a DI specification and popular frameworks, such as Spring, facilitate DI usage in software projects. However, bad DI implementation practices can have negative consequences, such as increasing coupling, hindering the achievement of DI's main goal. Even though the literature suggests the existence of DI anti-patterns, there is no detailed documentation of such bad practices. Moreover, there is no evidence on their occurrence and perceived usefulness from the developer's point of view. </p> <p><strong>Aims</strong> Our goal is to review the reported DI anti-patterns in order to analyze their completeness and to propose and evaluate a novel catalog of Java DI anti-patterns. </p> <p><strong>Method</strong> We propose a catalog containing twelve Java DI anti-patterns. We selected four open-source and two closed-source software projects that adopt a DI framework and developed a tool to statically analyze the occurrence of the candidate DI anti-patterns within their source code. Also, we conducted a survey through face to face interviews with three experienced developers that regularly apply DI. We extended the survey in order to gather the perception of a set of fifteen expert and novice developers through an online questionnaire. </p> <p><strong>Results</strong> At least nine different DI anti-patterns appeared frequently in the analyzed projects. In addition, the feedback received from the developers confirmed the relevance of the catalog. Besides, the respondents expressed their willingness to refactor instances of anti-patterns from source code.</p> <p><strong>Conclusions</strong> The catalog contains Java DI anti-patterns that occur in practice and are useful. Sharing it with practitioners may help them to avoid such anti-patterns.</p>
Dataset for paper "Automatically Identifying Archival-worthy, Software-related Slack Conversations"
<p>This dataset consists of 2000 conversations from 5 programming related Q&A channels, hosted on Slack, and accompanies the paper "Automatically Identifying Archival-worthy, Software-related Slack Conversations". In addition to the text of the conversations, each conversation has been annotated as either archival worthy or not. Our definition of archival-worthiness is:</p> <p><em>"If a conversation contains information that could be useful to other users, whether in the Slack channel or elsewhere, then it should be archived. These conversations have no determinate length and no need for objectivity. A conversation should be archived based on the availability and ease of identifying information that could help a person to gain useful software-related knowledge."</em></p> <p><strong>Data Origin: </strong>Numerous public Slack chat channels (<a href="https://slack.com/">https://slack.com/</a>) have recently become available that are focused on specific software engineering-related discussion topics, e.g., Python Development (<a href="https://pyslackers.com/web/slack">https://pyslackers.com/web/slack</a>). The data reflects a portion of the conversations on public channels related to Python, Clojure, Elm and Racket programming.</p> <p><strong>Data Pre-Processing:</strong> To protect privacy, we replace usernames with fake names, and replace absolute times with relative times (in seconds). The conversations are disentangled from the overall chat stream with each unique <em>thread </em>in the dataset specifying a conversation in the channel. Archival-worthy conversations are marked with 1, while non-archival-worthy with 0.</p>
Figure 77 in DELTA for Beginners. An introduction into the taxonomy software package DELTA
Figure 77. For the second set of taxa the identification is finished and another endpoint of the key is reached.
Figure 74 in DELTA for Beginners. An introduction into the taxonomy software package DELTA
Figure 74. Clicking on the Images button during the selection of character states will show the illustrations for all character states.
Figure 65 in DELTA for Beginners. An introduction into the taxonomy software package DELTA
Figure 65. The first character separated the taxa into two groups of about equal size. For the Eliminated Taxa the selected character state did not match.
Figure 79. Character 20 in DELTA for Beginners. An introduction into the taxonomy software package DELTA
Figure 79. Character 20 is dependent on character 18. After selecting the character state 'produced' in character 18, the character state dialog box appears for a selection of a character state of character 20.
Figure 29 in DELTA for Beginners. An introduction into the taxonomy software package DELTA
Figure 29. Directive file printnr for the output of taxon names used in a DELTA database. The numbers to the left of the directive file indicate different classes of directives (see in Table 2).
Figure 28 in DELTA for Beginners. An introduction into the taxonomy software package DELTA
Figure 28. Directive file printcr for the output of characters used in a DELTA database. Th e numbers to the left of the directive file indicate different classes of directives (see in Table 1).
Figure 25 in DELTA for Beginners. An introduction into the taxonomy software package DELTA
Figure 25. Confor in the DELTA Editor asks the user to make a selection of directive files being exported.
Figure 30 in DELTA for Beginners. An introduction into the taxonomy software package DELTA
Figure 30. Directive file toint for generating the files needed for Intkey. Th e numbers to the left of the directive file indicate different classes of directives (see Table 3). Th e grey ovals show commands where input of the user might be required. (continued on next page)
Figure 34 in DELTA for Beginners. An introduction into the taxonomy software package DELTA
Figure 34. The ofiles directive file contains data for the automatic naming of files created with tonatsr. The numbers to left of the directive file indicate different classes of directives (see in Table 7). Th e grey oval shows command where input of the user might be required.
Figure 27a–b in DELTA for Beginners. An introduction into the taxonomy software package DELTA
Figure 27a–b. Information window of Confor informing the user of a successful output: a it was terminated correctly and b the path shows were the output files are located.
Figure 17a–g. Character state images. a in DELTA for Beginners. An introduction into the taxonomy software package DELTA
Figure 17a–g. Character state images. a the Images tab in the Character editor b Settings allow the selection of the path to the image directory and font details for the overlays c Display shows the selected image file in a window with the character and overlay boxes d feature text of the character e Hotspot selection box f character state overlay box g Cancel box. Th ese overlays are used in Intkey.
Figure 31 in DELTA for Beginners. An introduction into the taxonomy software package DELTA
Figure 31. The tonatr directive file contains the commands for producing natural language descriptions. The numbers to the left of the directive file indicate different classes of directives (see in Table 4). The grey ovals show commands where input of the user might be required. (continued on next page).
Figure 13. Inserting a in DELTA for Beginners. An introduction into the taxonomy software package DELTA
Figure 13. Inserting a taxon that was marked as a variant (Treat as variant) in the Taxon editor, indicated by (+) preceding the taxon name.
Figure 14a–h in DELTA for Beginners. An introduction into the taxonomy software package DELTA
Figure 14a–h. Attribute editor in the Grid view. a character feature text b taxon list c selection box shows character state 1 selected. Th e red dash of character 12 indicates that this character is inapplicable d the grey background in the box indicates that a comment in angle brackets was made to specify the character state e unrecorded character f character states explicitly marked unknown g character state pane, where aside from the input of the character state as a number comments can be made in angle brackets h character state selection check boxes.
Figure 12 in DELTA for Beginners. An introduction into the taxonomy software package DELTA
Figure 12. Recording the character states in the tree–like expanded character pane. It is possible to add comments in angle brackets, and other qualifying information, in the lower left pane.
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