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2,327 results for “Placement”
Fig. 3 in Phylogenetic placement of a new paleoendemic pill scarab from the Udzungwa Mountains, Tanzania, triggers biogeographic interpretations (Coleoptera: Hybosoridae, Ceratocanthinae)
Fig. 3 – Habitus of select ingroup and outgroup pill scarabs, dorsal view; images are to scale.
Data: The effect of external lateral stabilization on the use of foot placement to control mediolateral stability in walking and running
<p>Data and code for Mahaki et al. (2019): The effect of external lateral stabilization on the use of foot placement to control mediolateral stability in walking and running (<a href="https://doi.org/10.7717/peerj.7939">https://doi.org/10.7717/peerj.7939</a>).</p> <p>The Gas, Force, and Optotrak data.rar folder contains three subfolders as follows:</p> <p><strong>Gasdata2</strong> - contains all oxygen data, plus a scripts to run the data.</p> <p> - Subjectxx - folder with oxygen data</p> <p> - MainMohammadRunning_EC - script to analyze the oxygen data.</p> <p> - EC_walkRun_Stat - script to statistically test the hypotheses in terms of energetic cost. The results have been presented in supplementary material (<strong>Fig. S5.</strong>)</p> <p><strong>KinData</strong> - contains all kinematic and kinetic data (one folder per subject)</p> <p> - Marker.xlsx - info on which markers were placed where</p> <p> - Pointers.xlsx - info on which pointer trials contain which virtual markers</p> <p> - Trials.xlsx - info on which files contain which conditions</p> <p> - Subjectxx - folder with all the data.</p> <p> - The *.ndf files contain the kinematics (can be read with readndf.m, available in a subfolder of the VU 3d model (see below)</p> <p> - The *.afp files contain the raw voltage data from the force plates. These can be converted to forces and moments using the function FBW_dualbelt.m, available in a subfolder of the VU 3d model (see below).</p> <p> - The _HS.mat files contain calculated events (see script A below), and are normal matlab files.</p> <p><strong>Software</strong> - contains all code used to get from the kinematic data to outcome variables, script were ran as:</p> <p> - A_Main_Heelstrikes - script which calculates heelstrikes, and prompts the user to check these. Results are saved in the same folder (and under same name, but with extension HS.mat) as original data.</p> <p> - B_Main_Calculate_step - script which was used to calculate main outcomes for each subject and condition. results of this script are stored in foot_placement_thorax.mat and used in subsequent scripts.</p> <p> - C_Combine_Test_Legs - script which was used to statistically investigate the effect of leg and speed on R<sup>2</sup> time series (lines 67-69). The results have been presented in Supplementary Material file (<strong>Fig. S1.</strong>).</p> <p> - D_main_plot_WalkRun_normalOnly - script which was used to check our second hypothesis which was the comparison between normal walking and running in terms of foot placement strategy. The results have been presented in <strong>Fig 4. & 5.</strong>.</p> <p> - E_main_plot_WalkRun - script which was used to check our third and fourth hypotheses which we investigated the effect of external lateral stabilization on R<sup>2</sup> values in walking and running (hypothesis 3) and differences of external lateral stabilization effect between walking and running (i.e. mode of locomotion X condition interaction, hypothesis 4) during swing phase. The results have been presented in <strong>Fig 5. and Fig 7.</strong>.</p> <p> - SW_SWvariability_WalkRun - script which was used to check our hypotheses in terms of step width and step width variability. The results have been presented in <strong>Fig 6</strong>.</p> <p> - F_Supplementary_main_plot_run - script which was used to compare R<sup>2</sup> values between running trials (speed effect) and the results have been presented in supplementary material (<strong>Fig .S2.</strong>).</p>
Placement of Analog Integrated Circuits / Packing - synthetic instances
<p>Synthetically generated instances used in</p> <ul> <li>Automatic Placer for Analog Circuits Using Integer Linear Programming Warm Started by Graph Drawing 10.5220/0011789300003396</li> <li>Matheuristic Local Search for the Placement of Analog Integrated Circuits 10.1007/978-3-031-49662-2_10</li> <li>Automated placement of analog integrated circuits using priority-based constructive heuristic papers 10.1016/j.cor.2024.106643</li> </ul>
Data from: Phylotranscriptomics to bring the understudied into the fold: monophyletic Ostracoda, fossil placement and pancrustacean phylogeny
An ambitious, yet fundamental goal for comparative biology is to understand the evolutionary relationships for all of life. Yet many important taxonomic groups have remained recalcitrant to inclusion into broader scale studies. Here, we focus on collection of 9 new 454 transcriptome data sets from Ostracoda, an ancient and diverse group with a dense fossil record, which is often under-sampled in broader studies. We combine the new transcriptomes with a new morphological matrix (including fossils) and existing Expressed Sequence Tag (EST), mitochondrial genome, nuclear genome and rDNA data. Our analyses lead to new insights into ostracod and pancrustacean phylogeny. We obtained support for three epic pancrustacean clades that likely originated in the Cambrian: Oligostraca (Ostracoda, Mystacocarida, Branchiura, Pentastomida); Multicrustacea (Copepoda, Malacostraca, Thecostraca); and a clade we refer to as Allotriocarida (Hexapoda, Remipedia, Cephalocarida, Branchiopoda). Within the Oligostraca clade, our results support the unresolved question of ostracod monophyly. Within Multicrustacea, we find support for Thecostraca plus Copepoda, for which we suggest the name Hexanauplia. Within Allotriocarida, some analyses support the hypothesis that Remipedia is the sister taxon to Hexapoda, but others support Brachiopoda+Cephalocarida as the sister group of hexapods. In multiple different analyses, we see better support for equivocal nodes using slow-evolving genes or when excluding distant outgroups, highlighting the increased importance of conditional data combination in this age of abundant, often anonymous data. Yet, when we analyze the same set of species and ignore rate of gene evolution, we find higher support when including all data, more in line with a 'total evidence' philosophy. By concatenating molecular and morphological data, we place pancrustacean fossils in the phylogeny, which can be used for studies of divergence times in Pancrustacea, Arthropoda, or Metazoa. Our results and new data will allow for attributes of Ostracoda, such as its amazing fossil record and diverse biology, to be leveraged in broader scale comparative studies. Further, we illustrate how adding extensive next-generation sequence data from understudied groups can yield important new phylogenetic insights into long-standing questions, especially when carefully analyzed in combination with other data.
Data from: APPLES: Scalable distance-based phylogenetic placement with or without alignments
<p>Placing a new species on an existing phylogeny has increasing relevance to several applications. Placement can be used to update phylogenies in a scalable fashion and can help identify unknown query samples using (meta-)barcoding, skimming, or metagenomic data. Maximum likelihood (ML) methods of phylogenetic placement exist, but these methods are not scalable to reference trees with many thousands of leaves, limiting their ability to enjoy benefits of dense taxon sampling in modern reference libraries. They also rely on assembled sequences for the reference set and aligned sequences for the query. Thus, ML methods cannot analyze datasets where the reference consists of unassembled reads, a scenario relevant to emerging applications of genome-skimming for sample identification. We introduce APPLES, a distance-based method for phylogenetic placement. Compared to ML, APPLES is an order of magnitude faster and more memory efficient, and unlike ML, it is able to place on large backbone trees (tested for up to 200,000 leaves). We show that using dense references improves accuracy substantially so that APPLES on dense trees is more accurate than ML on sparser trees, where it can run. Finally, APPLES can accurately identify samples without assembled reference or aligned queries using kmer-based distances, a scenario that ML cannot handle. APPLES is available publically at github.com/balabanmetin/apples.</p>
Figures 1–2. Diolcus thomasi, habitus. 1 in A new species of Diolcus Mayr (Hemiptera: Heteroptera: Scutelleridae: Pachycorinae) with a reexamination of the subfamily and generic placement of Nesogenes boscii (Fabricius) (Hemiptera: Heteroptera: Scutelleridae: Elvisurinae or Pachycorinae)
Figures 1–2. Diolcus thomasi, habitus. 1) Dorsal view. 2) Ventral view. Scale line = 1.0 mm.
Figures 5–6. Nesogenes boscii, habitus. 5 in A new species of Diolcus Mayr (Hemiptera: Heteroptera: Scutelleridae: Pachycorinae) with a reexamination of the subfamily and generic placement of Nesogenes boscii (Fabricius) (Hemiptera: Heteroptera: Scutelleridae: Elvisurinae or Pachycorinae)
Figures 5–6. Nesogenes boscii, habitus. 5) Dorsal view. 6) Ventral view. Scale line = 1.0 mm.
Figures 3–4. Diolcus chrysorrhoeus, habitus. 3 in A new species of Diolcus Mayr (Hemiptera: Heteroptera: Scutelleridae: Pachycorinae) with a reexamination of the subfamily and generic placement of Nesogenes boscii (Fabricius) (Hemiptera: Heteroptera: Scutelleridae: Elvisurinae or Pachycorinae)
Figures 3–4. Diolcus chrysorrhoeus, habitus. 3) Dorsal view. 4) Ventral view. Scale line = 1.0 mm.
FIGURE 3 in Redescription, phylogenetic placement, and taxonomic reassignment of Mesobdella lineata (Sciacchitano, 1959) (Hirudinida: Arhynchobdellida)
FIGURE 3 (below). Parapraobdella lineata, n. gen. A. Dorsal surface of body
FIGURE 4 in Redescription, phylogenetic placement, and taxonomic reassignment of Mesobdella lineata (Sciacchitano, 1959) (Hirudinida: Arhynchobdellida)
FIGURE 4. Strict consensus of 12 equally parsimonious trees obtained from 32 morpho-
Figure 13 in An overview of labeonin relationships and the phylogenetic placement of the Afro-Asian genus Garra Hamilton, 1922 (Teleostei: Cyprinidae), with the description of five new species of Garra from Ethiopia, and a key to all African species
Figure 13. Garra geba, holotype, AMNH 228485, 86.4 mm standard length.
Figure 12 in An overview of labeonin relationships and the phylogenetic placement of the Afro-Asian genus Garra Hamilton, 1922 (Teleostei: Cyprinidae), with the description of five new species of Garra from Ethiopia, and a key to all African species
Figure 12. Garra duobarbis, holotype, AMNH 228484, 66.8 mm standard length.
Figure 11 in An overview of labeonin relationships and the phylogenetic placement of the Afro-Asian genus Garra Hamilton, 1922 (Teleostei: Cyprinidae), with the description of five new species of Garra from Ethiopia, and a key to all African species
Figure 11. Garra regressus, holotype, AMNH 228487, 121.8 mm standard length.
Figure 15 in An overview of labeonin relationships and the phylogenetic placement of the Afro-Asian genus Garra Hamilton, 1922 (Teleostei: Cyprinidae), with the description of five new species of Garra from Ethiopia, and a key to all African species
Figure 15. Garra dembecha, holotype, AMNH 228483, 78.8 mm standard length.
Figure 14 in An overview of labeonin relationships and the phylogenetic placement of the Afro-Asian genus Garra Hamilton, 1922 (Teleostei: Cyprinidae), with the description of five new species of Garra from Ethiopia, and a key to all African species
Figure 14. Garra tana, holotype, AMNH 223824, 108.3 mm standard length.
Advanced Optimal Sensor Placement for Kalman-based multiple-input estimation
<p>Data set for journal publication "Advanced Optimal Sensor Placement for Kalman-based input estimation".</p>
Data for: Phylogenetic placement and taxonomic revision of the enigmatic Brazilian genus Monochilus Fisch. & C. A. Mey. (Lamiaceae)
<p><em>Monochilus</em> (Lamiaceae) is an enigmatic genus endemic to Brazil with two rarely collected species currently recognized. Based on morphological features <em>Monochilus</em> is hypothesized to be closely related to <em>Amasonia</em> within subfamily Ajugoideae. However, <em>Monochilus</em> is one of the few genera within Lamiaceae never to be represented in a published molecular phylogenetic study and thus has an uncertain placement with the subfamily. During recent herbarium exploration in association with the Flora of Brasil 2020 project, new specimens of <em>Monochilus</em> <em>gloxinifolius</em> and <em>M</em>. <em>obovatus</em> were uncovered. Based on this material, a new phylogeny of Ajugoideae was constructed based on nuclear ribosomal ITS and the chloroplast markers matK and trnL-trnF. <em>Monochilus</em>, as previously hypothesized, is closely related to <em>Amasonia</em> and placed within Ajugoideae. We discuss the phylogenetic placement of the genus and provide a taxonomic revision with a description, distribution maps, an identification key, preliminary conservation assessments, photographic plates and comments on both the taxonomy and ecology of these two species. Additionally, we provide a lecotypification for <em>M</em>. <em>gloxinifolius</em>.</p>
Sanger sequences of marpissoid salticids for Kelawakaju placement
<p><span>The genus <em>Kelawakaju</em> Maddison & Ruiz, gen. nov., is described for a lineage of bark-dwelling Asian marpissine jumping spiders that represent a dispersal to Eurasia separate from that of the <em>Marpissa</em>-<em>Mendoza</em> lineage, according to the phylogeny recovered from analysis of four gene regions. All of the species of Kelawakaju are new except <em>K</em>. <em>frenata </em>(Simon, 1901), comb. nov., which is here transferred from <em>Ocrisiona</em> Simon, 1901. <em>K</em>. <em>frenata</em> is known from Hong Kong, Guangdong, Guangxi, and likely Taiwan. The five new species are <em>Kelawakaju</em> <em>mulu</em> Maddison & Ruiz (type species of Kelawakaju, from Sarawak, Malaysia, ♂♀), <em>K</em>. <em>intexta</em> Maddison & Ruiz (from Sarawak, ♂), <em>K</em>. <em>leucomelas</em> Maddison & Ng (Singapore and Johor Bahru, ♂♀), <em>K</em>. <em>sahyadri</em> Vishnudas, Maddison, & Sudhikumar (India, ♂♀), and <em>K</em>. <em>singapura</em> Maddison & Ng (Singapore, ♂♀), all sp. nov.</span></p>
HADES: An NFV solution for energy-efficient placement and resource allocation in heterogeneous infrastructures. Study dataset
<p>The publication and research associated with this dataset are currently under review in the Journal of Network and Computer Applications.</p> <p>In that research, we present HADES, an NFV solution for energy-efficient placement and resource allocation in heterogeneous infrastructures. HADES is an OSM (Open Source MANO) extension that allows the configuration of virtual network functions and their subsequent resource allocation and deployment at the edge, minimizing energy consumption and ensuring the quality of service.</p> <p>This dataset contains the following:</p> <ul> <li>1 CSV file with execution time results of the iTAREA module for (60) different problem sizes and (3) execution environments.</li> <li>1 CSV file with energy consumption results of HADES deployments and other 5 assignment policies: First-fit, Random-fit, Fastest-fit, Best-fit, and kube-scheduler (the Kubernetes’ assignment policy).</li> </ul> <p>This work is supported by the European Union's H2020 research and innovation programme under grant agreement DAEMON 101017109 and by the projects co-financed by FEDER funds LEIA UMA18-FEDERJA-15 and IRIS PID2021-122812OB-I00 (MCI/AEI).</p>
Adapting camera-trap placement based on animal behaviour for rapid detection: a focus on the Endangered, white-bellied pangolin (Phataginus tricuspis)
<p>Table containing detection data of species using two camera trap placement strategies (log vs non-log)</p>
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