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470 results for “tool use”
START Workshop - Use of Life Cycle Assessment as an Environmental Impact Tool
<p>Video from an internal workshop on Life Cycle Assessment that was held in June 2023 by 3drivers (speakers were Eduardo Santos and Ana Braga) as a basic training for other consortium members, with the goal of creating a common ground among partners for the subsequent environmental impact assessment activities that START will carry out on the thermoelectric solutions that will be delivered.</p> <p>The video is related to the general introduction given by E. Santos on the basics of the LCA approach and applications. It may be useful to you if new to the topic.</p>
Data and tools of the landscape and cost analysis of data repositories currently used by the Swiss research community
<p>This file collection is part of the ORD Landscape and Cost Analysis Project (DOI: 10.5281/zenodo.2643460), a study jointly commissioned by the SNSF and swissuniversities in 2018.</p> <p>Please cite this data collection as:<br> von der Heyde, M. (2019). Data and tools of the landscape and cost analysis of data repositories currently used by the Swiss research community. Retrieved from https://doi.org/10.5281/zenodo.2643495</p> <p>Connected data papers are:<br> von der Heyde, M. (2019). Open Data Landscape: Repository Usage of the Swiss Research Community: Description of collection, collected data, and analysis methods [Data paper]. Retrieved from https://doi.org/10.5281/zenodo.2643430<br> von der Heyde, M. (2019). International Open Data Repository Survey: Description of collection, collected data, and analysis methods [Data paper]. Retrieved from https://doi.org/10.5281/zenodo.2643450</p> <p>Connected data sets are:<br> von der Heyde, M. (2019). Data from the Swiss Open Data Repository Landscape survey. Retrieved from https://doi.org/10.5281/zenodo.2643487<br> von der Heyde, M. (2019). Data from the International Open Data Repository Survey. Retrieved from https://doi.org/10.5281/zenodo.2643493</p> <p> </p> <p><strong>Contact</strong></p> <p>Swiss National Science Foundation (SNSF)</p> <p>Open Research Data Group</p> <p>E-mail: <a href="mailto:ord@snf.ch">ord@snf.ch</a></p> <p> </p> <p>swissuniversities</p> <p>Program "Scientific Information"</p> <p>Gabi Schneider</p> <p>E-Mail: <a href="mailto:isci@swissuniversities.ch">isci@swissuniversities.ch</a></p>
Acoustic features as a tool to visualize and explore marine soundscapes: Applications illustrated using marine mammal Passive Acoustic Monitoring datasets
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Area and Timing data and R script for: 3D scanning as a tool to measure growth rates of live coral microfragments used for coral reef restoration
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Using species distribution models and decision tools to direct surveys and identify potential translocation sites for a critically endangered species
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Tool use aids prey-fishing in a specialist predator of stingless bees
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Data from: Tool use increases mechanical foraging success and tooth health in southern sea otters (Enhydra lutris nereis)
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Evaluating usefulness, ease of use and usability of an UML-based Software Product Line Tool
<p>Vídeo de apresentação do artigo "Evaluating usefulness, ease of use and usability of an UML-based Software Product Line Tool" para o 34° Simpósio Brasileiro de Engenharia de Software (SBES'20), 21-23 de Outubro de 2020, Natal, RN, Brasil. Autores: Leandro F. da Silva e Edson OliveiraJr.</p>
Benchmark data used in the evaluation of ChiRA tool-suite.
<p>The reads generated mimic CLASH experimental data. Each read is a fusion of a human hg38 miRBase mature miRNAs and some random TargetScan target sequences. The numbers 10, 12, 15, 18, and 20 in the file names represent the length of the chimeric arms. The are 1million reads in FASTA file. Files with "Insert" in their names contain a short 5 nt random sequence, whereas the "noInsert" files do not. TargetScanSites_merged.fa.fasta and hg38_MIR_mature.fa.fasta contain the reference sequences. The sequence identifiers in the FASTA file are in the following format:</p> <p>>hsa-miR-193b-5p_MIMAT0004767:1-20||chr7:114656010-114656173+:82-95</p> <p>where,</p> <ul> <li>hsa-miR-193b-5p_MIMAT0004767 is the sequence ID of the miRNA from which first chimeric arm of this read was derived from. This ID can be found in hg38_MIR_mature.fa.fasta.</li> <li>1-20 represents the 1-based start and end positions on hsa-miR-193b-5p_MIMAT0004767 representing the origin of the first chimeric arm.</li> <li>chr7:114656010-114656173+ is the sequence ID of the TargetScan target site from which the second chimeric arm of this read was derived from. This ID can be found in TargetScanSites_merged.fa.fasta</li> <li>82-95 represents the 1-based start and end positions on chr7:114656010-114656173+ representing the origin of the second chimeric arm.</li> </ul>
THESIS Tools Datasets: Land Use Tool - CLM5
<p>NCAR is coordinating the development of the Toolbox for Human-Earth System Integration and Scaling (THESIS) to facilitate linkages between the Community Earth System Model (CESM) and Integrated Assessment or impact models. THESIS consists of models and software tools to translate, scale, and synthesize information from and between human system models and CESM.</p> <p>Code and documentation for the Land Use Tool - CLM5 is currently hosted on github: https://github.com/lawrencepj1/clm5landusedatatool</p>
Clay models and eDNA are useful tools for identifying predators of Salamanders
<p class="MsoNormal">Clay models are a popular technique for studying predation in nature due to their ease of deployment and minimal disruption of natural processes, but a drawback is the ambiguity of identifying predators based on bite marks. However, it is possible to amplify and sequence environmental DNA (eDNA) from these bite marks and to identify the predators responsible for attacking models. In this study, we sought to test the viability of eDNA from clay models as a means of identifying predators. We deployed molded clay models that resemble <em><span>Plethodon ventralis</span></em> Highton (Southern Zigzag Salamanders) into the field. We then extracted eDNA from visible bite marks, amplified and sequenced the 12S rRNA mitochondrial locus on an Illumina MiSeq, and used BLAST to determine the identity of representative sequences. We identified likely predators as <em><span>Procyon lotor</span></em> L. (American Raccoons), <em><span>Didelphis virginiana</span></em> Kerr (Virginia Opossums), <em><span>Turdus migratorius</span></em> L. (American Robins), and <em><span>Tamias striatus</span></em> L. (Eastern Chipmunks). We believe that this technique is helpful for adding a layer of specificity to clay model studies, albeit with a few potential pitfalls that we discuss.</p>
GNSS-IR data for "Real-time water levels using GNSS-IR: a potential tool for flood monitoring"
<p>Organised SNR data used for GNSS-IR analysis in the article "Real-time water levels using GNSS-IR: a potential tool for flood monitoring" by David Purnell, Natalya Gomez, William Minarik and Gregory Langston.</p><p> </p><p>The directories 'rv3s' and 'sjdlr' contain SNR data corresponding to sites Trois-Rivières and Saint-Joseph-de-la-Rive, respectively.</p><p> </p><p>Software for processing the data can be found at: https://github.com/purnelldj/gnssir_rt</p><p> </p><p>SNR data is given as text files in the format specified here except for columns 4+:</p><p>https://gnssrefl.readthedocs.io/en/latest/pages/file_structure.html#the-snr-data-format</p><p>columns:</p><p>1. sat PRN with an offset such that GLONASS satellites are between 100-200 and Galileo are between 200-300</p><p>2. satellite elevation (degrees)</p><p>3. azi is satellite azimuth (degrees)</p><p>4. GPS time (seconds since 1980)</p><p>5. L1 SNR</p>
PPARδ dataset curated and enriched using the Enalos tools and Enalos KNIME nodes for machine learning analysis (SCENARIOS project)
<p><span>A curated and enriched dataset for PPAR</span>δ<span>, suitable for in silico model development, was obtained from PubChem BioAssay under the numeric identifier AID 469785 using Enalos tools and Enalos KNIME nodes. This dataset comprises 136 compounds that induce luciferase activity, serving as an indicator of agonist activity against the human PPAR</span>δ<span> ligand-binding domain. These molecules were tested in a human embryonic kidney cell line (293T), co-transfected with a chimeric plasmid containing the yeast GAL4 DNA-binding domain (DBD). All 136 oxazole-based compounds retrieved from the dataset are accompanied by their half-maximal effective concentration (EC50) and enriched with 777 molecular descriptors extracted from their 2D structure using EnalosMold2 KNIME nodes</span></p>
Data from: Evaluating genotyping-in-thousands by sequencing as a genetic monitoring tool for a climate sentinel mammal using non-invasive and archival samples
<p>Genetic tools for wildlife monitoring can provide valuable information on spatiotemporal population trends and connectivity, particularly in systems experiencing rapid environmental change. Though many DNA sequencing approaches still require high quality and quantity of DNA obtained from traditional sources (e.g. blood and tissue), rapid genotyping tools such as Genotyping-in-Thousands by sequencing (GT-seq) have improved our ability to make use of degraded and less concentrated DNA commonly obtained from non-invasive and archival samples. Here, we developed a multi-purpose GT-seq panel (307 single nucleotide polymorphisms) for a climate sentinel mammal (the American pika, <em>Ochotona princeps</em>) for use as a genetic tool for monitoring populations in the Canadian Rocky Mountains. We optimized the panel using contemporary tissue samples (n = 77) and subsequently applied it to archival tissue (n = 17) and contemporary fecal pellet samples (n = 129) to evaluate its effectiveness at identifying individuals and sex, estimating relatedness, and inferring population structure. The panel demonstrated high efficacy with contemporary and archival tissue samples (94.7% and 90.5% genotyping success, respectively) and negligible genotyping error (0.001% and 0.0%, respectively). Despite relatively high genotyping success for fecal pellet samples (79.7%), high genotyping error (28.4%) limited its power as a monitoring tool to assess genetic variation using non-invasive samples and highlighted the need for further optimization around sample and data collection.</p>
Results of mining Rhodococcus genomes using antiSMASH tool.
<p>A collection of genbank files obtained from 14 <em>Rhodococcus</em> genomes.<br>Biosynthetic Gene Clusters generated using antiSMASH v7.1.</p> <p><em>Rhodococcus ruber</em> : <em>R. ruber</em> MSA14, <em>R. ruber</em> C1,<em> R. ruber </em>Chol-4, <em>R. ruber</em> P14,<em> R. ruber</em> ZM15.</p> <p><em>Rhodococcus corynebacterioides</em> NBRC 14404, <em>Rhodococcus fascians</em> D188, <em>Rhodococcus hoagii</em> 103S DE0411 (recently reclassified as <em>Prescottella equi)</em>, <em>Rhodococcus jostii</em> RHA1,<em> Rhodococcus erythropolis </em>R138, <em>Rhodococcus qingshengii </em>CS98, <em>Rhodococcus aetherivoran</em>s CBO21-1, <em>Rhodococcus gordoniae </em>NCTC13296, and <em>Rhodococcus pyridinivorans</em> SB3094.</p> <p> </p>
Mesolithic Plant Processing Unveiled: Multiscale Use-Wear Analysis of the Ground Stone Tools from Vlasac (Serbia)
<p>This repository contains the raw data and code to reproduce the analyses presented in the paper "Mesolithic Plant Processing Unveiled: Multiscale Use-Wear Analysis of the Ground Stone Tools from Vlasac (Serbia)" by Zupancich et al.</p> <p>The repositiory includes:</p> <ul> <li>CSV files containing the raw data of:</li> <li>3D surface measurement of experimental and archaeological ground stone tools</li> <li>Use wear spatial distribution</li> <li>Ground stone tools techno-morphological data</li> <li>HTML files of the code utilised to perform the analyses</li> </ul>
APPENDIX 3 in Finite element analysis of the proximal phalanx of the thumb in Hominoidea during simulated stone tool use
<p>APPENDIX 3. — Mesh-weighted arithmetic mean (<b>MWAM</b>), mesh-weighted median (<b>MWM</b>), quartiles values (<b>Q25</b>, <b>50</b>, <b>75</b> and <b>95</b>), percentage error of the arithmetic mean (<b>PEofAM</b>) and percentage error of the median (<b>PEofM</b>) for each species and loading scenario, under chimpanzee-scaled conditions.</p><table><tbody><tr><th>SPECIE</th><th>SCENARIO</th><th><b>N of Elements</b></th><th><b>MWAM</b></th><th><b>MWM</b></th><th><b>Q25</b></th><th><b>Q50</b></th><th><b>Q75</b></th><th><b>M95</b></th><th><b>PEofAM</b></th><th><b>PEofM</b></th></tr></tbody><tbody><tr><th>Chimpanzee</th><td>1</td><td>160104</td><td>8.0122</td><td>7.6599</td><td>4.2909</td><td>7.8345</td><td>11.4830</td><td>14.6530</td><td>0.0387</td><td>2.2794</td></tr><tr><th>Chimpanzee</th><td>2</td><td>160104</td><td>5.7312</td><td>5.4881</td><td>3.0880</td><td>5.6170</td><td>8.2101</td><td>10.4363</td><td>0.0341</td><td>2.3483</td></tr><tr><th>Chimpanzee</th><td>3</td><td>160104</td><td>8.0771</td><td>7.7090</td><td>4.3233</td><td>7.8865</td><td>11.5780</td><td>14.7960</td><td>0.0417</td><td>2.3024</td></tr><tr><th>Chimpanzee</th><td>4</td><td>160104</td><td>5.8607</td><td>5.5899</td><td>3.1557</td><td>5.7215</td><td>8.3844</td><td>10.7170</td><td>0.0419</td><td>2.3534</td></tr><tr><th>Modern Human</th><td>1</td><td>225743</td><td>7.5983</td><td>5.4469</td><td>3.0316</td><td>5.5620</td><td>11.3770</td><td>19.8150</td><td>0.7364</td><td>2.1135</td></tr><tr><th>Modern Human</th><td>2</td><td>225743</td><td>5.3623</td><td>3.8494</td><td>2.1389</td><td>3.9323</td><td>8.0325</td><td>13.9420</td><td>0.7334</td><td>2.1536</td></tr><tr><th>Modern Human</th><td>3</td><td>225720</td><td>7.6821</td><td>5.4907</td><td>3.0617</td><td>5.6072</td><td>11.4980</td><td>20.0690</td><td>0.7328</td><td>2.1222</td></tr><tr><th>Modern Human</th><td>4</td><td>225689</td><td>5.5209</td><td>3.9340</td><td>2.1951</td><td>4.0167</td><td>8.2813</td><td>14.4290</td><td>0.7156</td><td>2.1020</td></tr><tr><th>Neanderthal</th><td>1</td><td>240469</td><td>7.5408</td><td>5.7398</td><td>3.1415</td><td>5.8463</td><td>10.7260</td><td>19.1300</td><td>1.6003</td><td>1.8559</td></tr><tr><th>Neanderthal</th><td>2</td><td>240461</td><td>5.3229</td><td>4.0535</td><td>2.2448</td><td>4.1316</td><td>7.5691</td><td>13.4480</td><td>1.5817</td><td>1.9264</td></tr><tr><th>Neanderthal</th><td>3</td><td>240469</td><td>7.6103</td><td>5.7887</td><td>3.1663</td><td>5.8917</td><td>10.8170</td><td>19.3540</td><td>1.6076</td><td>1.7799</td></tr><tr><th>Neanderthal</th><td>4</td><td>240460</td><td>5.4615</td><td>4.1433</td><td>2.2936</td><td>4.2210</td><td>7.7516</td><td>13.9010</td><td>1.6017</td><td>1.8739</td></tr><tr><th>Gorilla</th><td>1</td><td>327267</td><td>7.5848</td><td>6.5180</td><td>4.1315</td><td>6.6614</td><td>10.0078</td><td>15.9652</td><td>0.1499</td><td>2.2001</td></tr><tr><th>Gorilla</th><td>2</td><td>327267</td><td>5.3112</td><td>4.5847</td><td>2.9071</td><td>4.6850</td><td>6.9811</td><td>11.1340</td><td>0.1473</td><td>2.1877</td></tr><tr><th>Gorilla</th><td>3</td><td>327267</td><td>7.7032</td><td>6.5956</td><td>4.1665</td><td>6.7425</td><td>10.1980</td><td>16.2770</td><td>0.1521</td><td>2.2272</td></tr><tr><th>Gorilla</th><td>4</td><td>327267</td><td>5.5459</td><td>4.7386</td><td>2.9746</td><td>4.8493</td><td>7.3571</td><td>11.7390</td><td>0.1536</td><td>2.3361</td></tr><tr><th>Orangutan</th><td>1</td><td>199857</td><td>7.9291</td><td>6.5783</td><td>4.2297</td><td>6.7471</td><td>10.3643</td><td>18.0617</td><td>0.6350</td><td>2.5660</td></tr><tr><th>Orangutan</th><td>2</td><td>199857</td><td>5.6296</td><td>4.6925</td><td>3.0326</td><td>4.8168</td><td>7.3231</td><td>12.7377</td><td>0.6308</td><td>2.6495</td></tr><tr><th>Orangutan</th><td>3</td><td>199782</td><td>8.0098</td><td>6.6472</td><td>4.2716</td><td>6.8239</td><td>10.4630</td><td>18.2554</td><td>0.6575</td><td>2.6582</td></tr><tr><th>Orangutan</th><td>4</td><td>199782</td><td>5.7884</td><td>4.8286</td><td>3.1119</td><td>4.9592</td><td>7.5206</td><td>13.1060</td><td>0.6481</td><td>2.7040</td></tr><tr><th>Gibbon</th><td>1</td><td>311442</td><td>12.1044</td><td>10.4260</td><td>6.1984</td><td>10.5940</td><td>16.2630</td><td>26.8950</td><td>0.1734</td><td>1.6114</td></tr><tr><th>Gibbon</th><td>2</td><td>311431</td><td>8.6667</td><td>7.4740</td><td>4.4483</td><td>7.5885</td><td>11.6390</td><td>19.2340</td><td>0.1762</td><td>1.5325</td></tr><tr><th>Gibbon</th><td>3</td><td>311442</td><td>12.1825</td><td>10.4940</td><td>6.2322</td><td>10.6650</td><td>16.3650</td><td>27.0820</td><td>0.1744</td><td>1.6295</td></tr><tr><th>Gibbon</th><td>4</td><td>311442</td><td>8.8241</td><td>7.6109</td><td>4.5179</td><td>7.7380</td><td>11.8330</td><td>19.6238</td><td>0.1753</td><td>1.6704</td></tr></tbody></table>
APPENDIX 2 in Finite element analysis of the proximal phalanx of the thumb in Hominoidea during simulated stone tool use
<p>APPENDIX 2. — Number of elements (N elements), mesh-weighted arithmetic mean (<b>MWAM</b>), mesh-weighted median (<b>MWM</b>), quartiles values (<b>Q25</b>, <b>50</b>, <b>75</b> and <b>95</b>), percentage error of the arithmetic mean (<b>PEofAM</b>) and percentage error of the median (<b>PeofM</b>) for each species and loading scenario, under human-scaled conditions.</p><table><tbody><tr><th>INDIVIDUAL</th><th>SCENARIO</th><th><b>N of Elements</b></th><th><b>MWAM</b></th><th><b>MWM</b></th><th><b>Q25</b></th><th><b>Q50</b></th><th><b>Q75</b></th><th><b>M95</b></th><th><b>PEofAM</b></th><th><b>PEofM</b></th></tr></tbody><tbody><tr><th>Modern Human</th><td>1</td><td>225689</td><td>3.7540</td><td>2.6128</td><td>1.3997</td><td>2.6690</td><td>5.6844</td><td>10.0261</td><td>0.7130</td><td>2.1509</td></tr><tr><th>Modern Human</th><td>2</td><td>225729</td><td>2.5238</td><td>1.7800</td><td>0.9680</td><td>1.8227</td><td>3.8100</td><td>6.6442</td><td>0.7309</td><td>2.3997</td></tr><tr><th>Modern Human</th><td>3</td><td>225689</td><td>3.8349</td><td>2.6530</td><td>1.4269</td><td>2.7080</td><td>5.8135</td><td>10.2790</td><td>0.7100</td><td>2.0714</td></tr><tr><th>Modern Human</th><td>4</td><td>225710</td><td>2.6876</td><td>1.8662</td><td>1.0241</td><td>1.9051</td><td>4.0670</td><td>7.1455</td><td>0.7225</td><td>2.0867</td></tr><tr><th>Neanderthal</th><td>1</td><td>240478</td><td>3.7401</td><td>2.7851</td><td>1.5604</td><td>2.8336</td><td>5.3814</td><td>9.6489</td><td>1.6161</td><td>1.7432</td></tr><tr><th>Neanderthal</th><td>2</td><td>240469</td><td>2.5277</td><td>1.8985</td><td>1.0995</td><td>1.9326</td><td>3.6118</td><td>6.4210</td><td>1.5858</td><td>1.7975</td></tr><tr><th>Neanderthal</th><td>3</td><td>240469</td><td>3.8275</td><td>2.8449</td><td>1.6271</td><td>2.8931</td><td>5.4883</td><td>9.8692</td><td>1.6163</td><td>1.6943</td></tr><tr><th>Neanderthal</th><td>4</td><td>240471</td><td>2.6708</td><td>1.9879</td><td>1.1443</td><td>2.0203</td><td>3.8108</td><td>6.8892</td><td>1.6184</td><td>1.6299</td></tr><tr><th>Chimpanzee</th><td>1</td><td>160103</td><td>4.1812</td><td>3.9750</td><td>2.2535</td><td>4.0610</td><td>5.9939</td><td>7.6454</td><td>0.0015</td><td>2.1631</td></tr><tr><th>Chimpanzee</th><td>2</td><td>160104</td><td>2.8698</td><td>2.7413</td><td>1.5694</td><td>2.8039</td><td>4.0960</td><td>5.1944</td><td>0.0004</td><td>2.2836</td></tr><tr><th>Chimpanzee</th><td>3</td><td>160046</td><td>4.2475</td><td>4.0192</td><td>2.2864</td><td>4.1141</td><td>6.0832</td><td>7.7941</td><td>0.0148</td><td>2.3599</td></tr><tr><th>Chimpanzee</th><td>4</td><td>160104</td><td>3.0042</td><td>2.8468</td><td>1.6410</td><td>2.9113</td><td>4.2753</td><td>5.4869</td><td>0.0164</td><td>2.2646</td></tr><tr><th>Gorilla</th><td>1</td><td>225710</td><td>2.6876</td><td>1.8662</td><td>1.0241</td><td>1.9051</td><td>4.0670</td><td>7.1455</td><td>0.7225</td><td>2.0867</td></tr><tr><th>Gorilla</th><td>2</td><td>327267</td><td>2.4440</td><td>2.1049</td><td>1.3316</td><td>2.1522</td><td>3.1882</td><td>5.1728</td><td>0.1482</td><td>2.2471</td></tr><tr><th>Gorilla</th><td>3</td><td>327267</td><td>3.7738</td><td>3.1737</td><td>1.9572</td><td>3.2548</td><td>5.0131</td><td>8.1784</td><td>0.1610</td><td>2.5570</td></tr><tr><th>Gorilla</th><td>4</td><td>327267</td><td>2.6870</td><td>2.2688</td><td>1.3987</td><td>2.3215</td><td>3.5807</td><td>5.7799</td><td>0.1603</td><td>2.3228</td></tr><tr><th>Orangutan</th><td>1</td><td>199857</td><td>4.0409</td><td>3.3878</td><td>2.1630</td><td>3.4804</td><td>5.2597</td><td>9.1689</td><td>0.6450</td><td>2.7344</td></tr><tr><th>Orangutan</th><td>2</td><td>199857</td><td>2.7519</td><td>2.3201</td><td>1.5089</td><td>2.3899</td><td>3.5526</td><td>6.1413</td><td>0.6300</td><td>3.0085</td></tr><tr><th>Orangutan</th><td>3</td><td>199813</td><td>4.1216</td><td>3.4543</td><td>2.2075</td><td>3.5543</td><td>5.3691</td><td>9.3611</td><td>0.6596</td><td>2.8941</td></tr><tr><th>Orangutan</th><td>4</td><td>199813</td><td>2.9129</td><td>2.4571</td><td>1.5893</td><td>2.5330</td><td>3.7670</td><td>6.5330</td><td>0.6369</td><td>3.0885</td></tr><tr><th>Gibbon</th><td>1</td><td>311431</td><td>6.3313</td><td>5.4576</td><td>3.2272</td><td>5.5294</td><td>8.5269</td><td>14.0750</td><td>0.1785</td><td>1.3156</td></tr><tr><th>Gibbon</th><td>2</td><td>311442</td><td>4.3431</td><td>3.7514</td><td>2.2259</td><td>3.8016</td><td>5.8425</td><td>9.6143</td><td>0.1738</td><td>1.3370</td></tr><tr><th>Gibbon</th><td>3</td><td>311442</td><td>6.4105</td><td>5.5281</td><td>3.2583</td><td>5.6069</td><td>8.6284</td><td>14.2694</td><td>0.1767</td><td>1.4247</td></tr><tr><th>Gibbon</th><td>4</td><td>311442</td><td>4.5087</td><td>3.9023</td><td>2.3007</td><td>3.9605</td><td>6.0438</td><td>10.0180</td><td>0.1783</td><td>1.4927</td></tr></tbody></table>
TABLE 3 in Finite element analysis of the proximal phalanx of the thumb in Hominoidea during simulated stone tool use
<p>TABLE 3. — Mesh characteristics for each one of the specimens.Abbreviations: <b>a</b>, volume of the cortical bone; <b>b</b>, volume of trabecular bone; <b>c</b>, number of elements used to create the mesh for each FE model.</p><table><tbody><tr><th><b>Specimen</b></th><th><b>Volume CB (mm</b> <b>3</b><b>)</b> <b>a</b></th><th><b>Volume TB (mm</b> <b>3</b><b>)</b> <b>b</b></th><th><b>N <b>elementsc</b></b></th></tr></tbody><tbody><tr><th>Modern human</th><td>1012.8</td><td>651.1</td><td>225729</td></tr><tr><th>Neanderthal</th><td>733.3</td><td>662.6</td><td>240469</td></tr><tr><th>Chimpanzee</th><td>1046.1</td><td>178.6</td><td>160103</td></tr><tr><th>Gorilla</th><td>1642.9</td><td>577.9</td><td>225710</td></tr><tr><th>Orangutan</th><td>610.1</td><td>542.8</td><td>199857</td></tr><tr><th>Gibbon</th><td>250.7</td><td>65.9</td><td>311431</td></tr></tbody></table>
APPENDIX 1 in Finite element analysis of the proximal phalanx of the thumb in Hominoidea during simulated stone tool use
<p>APPENDIX 1. — Loads applied to the models for each one of the species under analysis and simulated loading scenarios. Abbreviations: <b>a</b>, forces (<b>N</b>) and angles (Ɵ) relative to the longitudinal axes of the bone; <b>b</b>, muscle forces for the human and chimpanzee reference models, respectively, are separate by a slash; <b>c</b>, force reactions in the proximal and distal joints were scaled to remove size effects when computing stress distributions.</p><table><tbody><tr><th>Specimen</th><th>SC</th><th>HRFa</th><th>FPB HS /FPB PTb</th><th>AP HS /AP PTb</th><th>EPB HS /EPB PTb</th><th>ABP HS /ABP PTb</th><th>JRFc d</th><th></th><th><b><b>JRFc</b> mc</b></th><th></th></tr></tbody><tbody><tr><th></th><td></td><td><b>N</b></td><td>Ɵ</td><td><b>N</b></td><td>Ɵ</td><td><b>N</b></td><td>Ɵ</td><td><b>N</b></td><td>Ɵ</td><td><b>N</b></td><td>Ɵ</td><td><b>N</b></td><td>Ɵ</td><td><b>N</b></td><td>Ɵ</td></tr><tr><th>Modern Human</th><td>1 2 3 4</td><td>3.92 7.65 3.92 7.65</td><td>90 90 45 45</td><td>17.95/37.20 13.49/27.95 17.95/37.20 13.49/27.95</td><td>45 45 45 45</td><td>38.79/66.43 29.15/49.91 38.79/66.43 29.15/49.91</td><td>61.2 61.2 61.2 61.2</td><td>4.33/28.75 2.74/18.18 4.33/28.75 2.74/18.18</td><td>16.7 16.7 16.7 16.7</td><td>5.28/35.94 3.34/22.72 5.28/35.94 3.34/22.72</td><td>180 180 180 180</td><td>44.06/89.27 28.26/61.46 45.21/90.33 30.70/63.62</td><td>180 180 180 180</td><td>38.81/114.1 28.02/78.76 37.96/113.3 26.36/77.14</td><td>180 180 180 180</td></tr><tr><th>Neanderthal</th><td>1 2 3 4</td><td>3.92 7.65 3.92 7.65</td><td>90 90 45 45</td><td>14.47/29.99 10.87/22.54 14.47/29.99 10.87/22.54</td><td>45 45 45 45</td><td>31.28/53.56 23.50/40.24 31.28/53.56 23.50/40.24</td><td>61.2 61.2 61.2 61.2</td><td>3.49/23.18 2.21/14.66 3.49/23.18 2.21/14.66</td><td>16.7 16.7 16.7 16.7</td><td>4.26/28.98 2.69/18.32 4.26/28.98 2.69/22.72</td><td>180 180 180 180</td><td>35.55/72.02 22.79/49.58 36.46/72.85 24.75/51.29</td><td>180 180 180 180</td><td>30.75/91.35 22.36/63.11 30.27/90.88 21.41/62.18</td><td>180 180 180 180</td></tr><tr><th>Chimpanzee</th><td>1 2 3 4</td><td>3.92 7.65 3.92 7.65</td><td>90 90 45 45</td><td>18.34/38.01 13.78/28.56 18.34/38.01 13.78/28.56</td><td>45 45 45 45</td><td>39.64/67.88 29.78/51.00 39.64/67.88 29.78/51.00</td><td>61.2 61.2 61.2 61.2</td><td>– – – –</td><td>– – – –</td><td>5.39/36.72 3.41/23.22 5.39/36.76 3.41/23.22</td><td>180 180 180 180</td><td>43.78/82.63 28.05/57.36 45.11/83.92 30.92/60.02</td><td>180 180 180 180</td><td>35.51/90.61 26.15/64.17 35.78/90.89 26.7/64.7</td><td>180 180 180 180</td></tr><tr><th>Gorilla</th><td>1 2 3 4</td><td>3.92 7.65 3.92 7.65</td><td>90 90 45 45</td><td>24.78/51.36 18.62/38.59 24.78/51.36 18.62/38.36</td><td>45 45 45 45</td><td>53.55/91.71 40.24/68.91 53.55/91.71 40.24/68.91</td><td>61.2 61.2 61.2 61.2</td><td>5.97/39.69 3.78/25.10 5.97/39.69 3.78/25.10</td><td>16.7 16.7 16.7 16.7</td><td>7.29/49.61 4.61/31.37 7.29/49.61 4.61/31.37</td><td>180 180 180 180</td><td>61.17/125.1 39.33/86.13 64.27/128.2 45.94/92.39</td><td>180 180 180 180</td><td>49.14/144.11 35.31/99.38 49.57/144.53 36.15/100.2</td><td>180 180 180 180</td></tr><tr><th>Orangutan</th><td>1 2 3 4</td><td>3.92 7.65 3.92 7.65</td><td>90 90 45 45</td><td>19.74/40.91 14.83/30.74 19.74/40.91 14.83/30.74</td><td>45 45 45 45</td><td>42.66/73.06 32.06/54.90 42.66/73.06 32.06/54.90</td><td>61.2 61.2 61.2 61.2</td><td>– – – –</td><td>– – – –</td><td>5.80/39.52 3.67/24.99 5.80/39.52 3.67/24.99</td><td>180 180 180 180</td><td>47.62/89.76 30.56/62.34 49.01/91.09 33.44/65.02</td><td>180 180 180 180</td><td>47.85/117.2 34.51/82.77 50.55/119.84 39.78/87.92</td><td>180 180 180 180</td></tr><tr><th>Gibbon</th><td>1 2 3 4</td><td>3.92 7.65 3.92 7.65</td><td>90 90 45 45</td><td>7.08/14.66 5.32/11.02 7.08/14.66 5.32/11.02</td><td>45 45 45 45</td><td>15.29/26.1 11.49/19.68 15.29/26.19 11.49/19.68</td><td>61.2 61.2 61.2 61.2</td><td>– – – –</td><td>– – – –</td><td>2.08/14.17 1.32/8.96 2.08/14.17 1.32/8.96</td><td>180 180 180 180</td><td>17.75/32.87 11.25/22.87 17.88/33.25 12.1/23.65</td><td>180 180 180 180</td><td>19.08/45.46 13.75/32.18 19.64/46.00 14.84/33.24</td><td>180 180 180 180</td></tr></tbody></table>
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