4,207 research outputs found
Cardozo AELJ Author Interview Series: Raven Berzal
No full textThe Cardozo AELJ Author Interview Series seeks to give our readers further insight into the Articles and Notes published in the Cardozo Arts & Entertainment Law Journal. In this interview, Raven Berzal discusses her Note, Accelerating Toward the Inevitable: How Covid-19 Helped Alter Traditional Models of Talent Compensation in the Film Industry, which was published in Volume 41, Issue 1.
This post was originally published on the Cardozo Arts & Entertainment Law Journal website on April 17, 2023. The original post can be accessed via the Archived Link button above
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Cardozo AELJ Author Interview Series: Raven Berzal
No full textThe Cardozo AELJ Author Interview Series seeks to give our readers further insight into the Articles and Notes published in the Cardozo Arts & Entertainment Law Journal. In this interview, Raven Berzal discusses her Note, Accelerating Toward the Inevitable: How Covid-19 Helped Alter Traditional Models of Talent Compensation in the Film Industry, which was published in Volume 41, Issue 1.
This post was originally published on the Cardozo Arts & Entertainment Law Journal website on April 17, 2023. The original post can be accessed via the Archived Link button above
Cardozo AELJ Author Interview Series: Raven Berzal
No full textThe Cardozo AELJ Author Interview Series seeks to give our readers further insight into the Articles and Notes published in the Cardozo Arts & Entertainment Law Journal. In this interview, Raven Berzal discusses her Note, Accelerating Toward the Inevitable: How Covid-19 Helped Alter Traditional Models of Talent Compensation in the Film Industry, which was published in Volume 41, Issue 1.
This post was originally published on the Cardozo Arts & Entertainment Law Journal website on April 17, 2023. The original post can be accessed via the Archived Link button above
SysBioChalmers/RAVEN: v2.7.5
No full textThe RAVEN Toolbox for genome scale model reconstruction, curation and analysis
SysBioChalmers/RAVEN: v2.9.1
No full text<ul>
<li>refactor:<ul>
<li>when running a unit test and a solver is not installed, report the absence of the solver, not the general failing of the test</li>
</ul>
</li>
<li>fix:<ul>
<li>prevent <code>glpk</code> timeout when running selected large FBA calculations</li>
<li>avoid an error when running <code>solveLP</code> in parallel and COBRA toolbox is not installed</li>
<li><code>getAllowedBounds</code> returned inconsistent results when running parallelization</li>
<li> various changes in relation to <code>solveLP</code> swapping the sign of reported objective function (<code>sol.f</code>), as already announced with RAVEN release <a href="https://github.com/SysBioChalmers/RAVEN/releases/tag/v2.7.12">2.7.12</a>, but not actually done at that point</li>
<li>ensure that RAVEN provided libSBML binaries are used, by using unique filenames</li>
<li><code>removeMets</code> also considers <code>metNotes</code> field if available</li>
<li><code>setParam</code> error message if incorrect paramType is specified</li>
</ul>
</li>
<li>feat:<ul>
<li><code>checkInstallation</code> reports how RAVEN was installed, as described in the <a href="https://github.com/SysBioChalmers/RAVEN/wiki/Installation#obtain-raven-toolbox">Wiki</a></li>
</ul>
</li>
<li>doc:<ul>
<li>minor changes in formatting of function documentation</li>
</ul>
</li>
</ul>
Sinopesa Raven & Schwendinger 1995
No full textGenus Sinopesa Raven & Schwendinger, 1995 Type species: Sinopesa maculata Raven & Schwendinger, 1995.Published as part of Lin, Yejie, Marusik, Yuri M., Gao, Caixia, Xu, Hao, Zhang, Xiaoqing, Wang, Ziyi, Zhu, Wenhui & Li, Shuqiang, 2021, Twenty-three new spider species (Arachnida: Araneae) from Asia, pp. 91-152 in Zoological Systematics 46 (2) on pages 114-115, DOI: 10.11865/zs.2021201, http://zenodo.org/record/536706
SysBioChalmers/RAVEN: v2.7.8
No full textfix:
findGeneDeletions report zero flux and growth ratio for essential genes
GitHub workflow parsing of testing output
feat:
removeRavenFromPath can quickly remove RAVEN folders from the MATLAB path
graph layout improvements for runPhenotypePhasePlane
runRobustnessAnalysis optional reduced cost plot
refactor:
setParam minor speed improvemen
SysBioChalmers/RAVEN: v2.9.2
No full text<ul>
<li>fix:<ul>
<li><code>checkInstallation</code> finding RAVEN when installed as MATLAB Add-On</li>
</ul>
</li>
</ul>
SysBioChalmers/RAVEN: v2.8.5
No full text<ul>
<li>feat:<ul>
<li>Distribute SoPlex binary for Windows with RAVEN, as another open-source alternative, slower than glpk, but suitable for MILP. Installation instructions are <a href="https://github.com/SysBioChalmers/RAVEN/wiki/Installation#solvers">updated</a>.</li>
<li><code>readYAMLmodel</code> should always make model.c-field, even if no objective function is specified (solves #509).</li>
<li><code>standardizeGrRules</code> should throw error if no grRules field is found.</li>
</ul>
</li>
<li>refactor:<ul>
<li><code>addRxnsGenesMets</code> more detailed error message if reactions cannot be found.</li>
<li><code>getAllowedBounds</code> use progressbar for reporting status.</li>
</ul>
</li>
</ul>
Responses to Raven matrices: Governed by visual complexity and centrality
No full textRaven matrices are widely considered a pure test of cognitive abilities. Previous research has examined the extent to which cognitive strategies are predictive of the number of correct responses to Raven items. This study examined whether response times can be explained directly from the centrality and visual complexity of the matrix cells (edge density and perceived complexity). A total of 159 participants completed a 12-item version of the Raven Advanced Progressive Matrices. In addition to item number (an index of item difficulty), the findings demonstrated a positive correlation between the visual complexity of Raven items and both the mean response time and the number of fixations on the matrix (a strong correlate of response time). Moreover, more centrally placed cells as well as more complex cells received more fixations. It is concluded that response times on Raven matrices are impacted by low-level stimulus attributes, namely, visual complexity and eccentricity.Human-Robot InteractionMedical Instruments & Bio-Inspired Technolog
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