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1,199 results for “Alignement”
Lacistorhynchidae family 28S alignment
<p><b>Aim:</b> Trypanorhyncha cestodes comprise a wide range of heteroxenous parasites infecting elasmobranchs as definitive hosts, with crustaceans, squids, and fishes acting as intermediate/paratenic hosts. Limited data exist on the larval infection of these cestodes and the role of intermediate and paratenic hosts in the life cycle of these parasites. In this study, we investigated the factors that determine the occurrence and the level of infection of <i>Grillotia</i> plerocerci in the skeletal muscles of various deep sea benthonic sharks and analysed the parasites through an integrative taxonomic approach.</p> <p><b>Location:</b> Gulf of Naples, Mediterranean Sea.</p> <p><b>Methods: </b>Sharks obtained as bycatch of commercial trawling activities (i.e., <i>Etmopterus spinax</i>, <i>Galeus melastomus </i>and <i>Scyliorhinus canicula</i>) were used in this study. Data from a limited number of <i>Dalatias licha</i> and <i>Scyliorhinus stellaris </i>were also included. <i>Grillotia </i>plerocerci were molecularly characterized using the p<span>artial 28S large subunit rDNA. B</span>oosted regression trees were used to model the relationship between the abundance of infection with both morphological and physiological predictors in each host.</p> <p><b>Results:</b> Plerocerci of <i>Grillotia </i>were detected in all shark species except <i>S. stellaris.</i> Host species significantly differed in terms of parasite abundance, with the highest and lowest prevalence and abundance of infection detected in <i>G. melastomus</i> and <i>E. spinax</i>, respectively. The relative influence of the traits involved in explaining the parasite abundance were related to the host size in <i>G</i>. <i>melastomus</i>, while both morphology- and physiology-related traits (e.g., gonadosomatic and hepatosomatic indices) explained the patterns observed in <i>E</i>. <i>spinax</i> and <i>S</i>. <i>canicula</i>. The 28S rDNA sequences shared identity of ∼99.40% with a <i>Grillotia</i> species previously found in the Mediterranean Sea. At intraspecific level, two different genotypes were found. A first type was retrieved only from <i>D. licha</i>, whereas a second type was found in <i>G. melastomus</i>, <i>E. spinax</i>,<i> </i>and<i> S. canicula</i>.</p> <p><b>Main conclusions:</b> Present results suggest that the two genotypes could be involved in different consumer-resource systems and confirm most of the examined shark species as transport hosts of <i>Grillotia</i> species for unknown larger top predators.</p>
The Dataset of Quantifying Alignment Deviations for the In-plane Biaxial Test System
<p><em><strong>For dataset in "alignmentDeviaitons_SP56_54976.csv":</strong></em></p> <p>The dataset consists of 12 alignment deviations of an in-plane biaxial tensile testing machine as well as 56 strain measurement points on cruciform specimens. A deep learning model is trained on the dataset to quantify 12 alignment deviations using 56 strain values on a shape-optimized cruciform specimen. The design of experiments includes Optimal Latin Hypercube, numerical modelling of Finite Element Methods. Using the Optimal Latin Hypercube, 55000 distinct groups of DOE simulation tests are constructed. Under the boundary conditions of 12 distinct deviations, 56 strain values at the required location on the cruciform specimen are obtained using Python scripts.</p> <p><em><strong>The illustration of “Code Scripts of Quantifying Alignment Deviations.rar”:</strong></em></p> <p>To quantify the alignment deviations of the in-plane biaxial testing machine, the AutoML model built-in AutoGluon was used to map relationship between the 12 alignment deviations of the in-plane biaxial testing machine and 56 strain measurement locations on a shape-optimized cruciform specimen. The training data for the AutoML model was obtained by Optimal Latin Hypercube, an algorithm-designed DOE experimental strategy. DOE scheme designed 12 alignment deviations of the in-plane biaxial testing machine. Through the finite element simulation of each group of alignment deviation in the DOE design scheme, 54976 groups of 56 strain values for the cruciform specimen were obtained.</p> <ol> <li><em><strong>AutogluonProgram_ SP56_ 54976 with_ Jupyter. ipynb: </strong></em>the operation procedure of developing the mapping relationship between alignment deviation and strain measurement locations using an automl model is documented in jupyerbook.</li> <li><em><strong>datasetOutput_ to_ localDir. py: </strong></em>output 56 strain measurement points and related 12 centering deviations to the local data file.</li> <li><em><strong>measurePointsSets_ in_ AbaqusModel. py: </strong></em>create a set of 56 measuring points for cruciform specimens in ABAQUS.</li> </ol>
Text-fig. 5. Anacardiaceae (a–m), Burseraceae (n–q). Scale bars = 1 cm. a–f: Pentoperculum sp. a–c: USNM PAL 772360. a: Lateral view of endocarp, apex up; three germination valves visible, the central clearly displaying the bipartite nature of the valve, reflected light, palladium coated. b: Apical view displaying six locules, with two preserved germination valves at the lower left, reflected light, palladium coated. c: Basal view of the endocarp, the locules suggested by swellings; note point of attachment, micro-CT scan surface rendering. d–f: Pentoperculum sp. USNM PAL 772359, reflected light, palladium coated. d: Lateral view of a probable 6-loculed endocarp, apex up; a single intact germination valve in the center, displaying the central lineation that divides it in two. e: Apical view; two bi-partite germination valves are visible, indicated by arrows to the middle cleavage line of two of the valves. f: Basal view, the locules suggested by the undulations in the margin. g–i: Indet. Spondioideae. USNM PAL 772358, reflected light, palladium coated. g: Lateral view of multi-locular endocarp, apex up. h: Apical view showing finely punctuate surface and peripheral locule cavities. i: Basal view. j–m: Cf. Pleiogynium USNM PAL 772357. j: Lateral view of the multi-locular endocarp, apex up; note intact germination valve on left and exposed locule facing the viewer, micro-CT scan surface rendering. k: Lateral view, rotated about 30° from (j), showing three exposed locules, reflected light, palladium coated; note bipartite locule lining at center. l: Apical view of the multilocular endocarp; the locule with intact germination valve at the upper right, reflected light, palladium coated. Arrows to each locule. m: Basal view showing central point of attachment and prominent radiating ridges aligned with the locules, micro-CT scan surface rendering. n–q: Canarium, USNM PAL 772361. Scale bar = 1 cm. n: Lateral view of endocarp directly facing one germination valve flanked by two strong ridges; apex up; specimen coated in sodium nitrate and photographed by R. A. Scott. o: Lateral view facing one of the three pronounced ridges, flanked to the left and right by two germination valves; apex up. p: Apical view displaying the three strong ridges, arching over the apex and flanking three deep embayments, covered with germination valves. q: Basal view, the three ridges being less pronounced. o–q: Reflected light, palladium coated. in The Early Middle Eocene Wagon Bed Carpoflora Of Central Wyoming, U.S.A.
Text-fig. 5. Anacardiaceae (a–m), Burseraceae (n–q). Scale bars = 1 cm. a–f: Pentoperculum sp. a–c: USNM PAL 772360. a: Lateral view of endocarp, apex up; three germination valves visible, the central clearly displaying the bipartite nature of the valve, reflected light, palladium coated. b: Apical view displaying six locules, with two preserved germination valves at the lower left, reflected light, palladium coated. c: Basal view of the endocarp, the locules suggested by swellings; note point of attachment, micro-CT scan surface rendering. d–f: Pentoperculum sp. USNM PAL 772359, reflected light, palladium coated. d: Lateral view of a probable 6-loculed endocarp, apex up; a single intact germination valve in the center, displaying the central lineation that divides it in two. e: Apical view; two bi-partite germination valves are visible, indicated by arrows to the middle cleavage line of two of the valves. f: Basal view, the locules suggested by the undulations in the margin. g–i: Indet. Spondioideae. USNM PAL 772358, reflected light, palladium coated. g: Lateral view of multi-locular endocarp, apex up. h: Apical view showing finely punctuate surface and peripheral locule cavities. i: Basal view. j–m: Cf. Pleiogynium USNM PAL 772357. j: Lateral view of the multi-locular endocarp, apex up; note intact germination valve on left and exposed locule facing the viewer, micro-CT scan surface rendering. k: Lateral view, rotated about 30° from (j), showing three exposed locules, reflected light, palladium coated; note bipartite locule lining at center. l: Apical view of the multilocular endocarp; the locule with intact germination valve at the upper right, reflected light, palladium coated. Arrows to each locule. m: Basal view showing central point of attachment and prominent radiating ridges aligned with the locules, micro-CT scan surface rendering. n–q: Canarium, USNM PAL 772361. Scale bar = 1 cm. n: Lateral view of endocarp directly facing one germination valve flanked by two strong ridges; apex up; specimen coated in sodium nitrate and photographed by R. A. Scott. o: Lateral view facing one of the three pronounced ridges, flanked to the left and right by two germination valves; apex up. p: Apical view displaying the three strong ridges, arching over the apex and flanking three deep embayments, covered with germination valves. q: Basal view, the three ridges being less pronounced. o–q: Reflected light, palladium coated.
Predicting Code Comprehension: A Novel Approach to Align Human Gaze with Code Using Deep Neural Networks
<p><strong>Checkout our Github-Repo for more information, issues, and pull requests: </strong></p> <p><a href="https://github.com/Taremeh/predicting-code-comprehension-eye-tracking/">https://github.com/Taremeh/predicting-code-comprehension-eye-tracking/</a></p> <p> </p> <p>Dataset and Replication Package for our paper "Predicting Code Comprehension: A Novel Approach to Align Human Gaze with Code Using Deep Neural Networks"</p>
Supplementary material - Dietary intake of adolescents and alignment with recommendations for healthy and sustainable diets: results of the SI.Menu study
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Unsupervised functional alignment via data-driven ANN-based visual decoding
<p>This repository is for the under-review paper "Unsupervised functional alignment via data-driven ANN-based visual decoding". Xin-Ya Zhang, Hang Lin, Zeyu Deng, Markus Siegel, Earl K. Miller and Gang Yan.</p>
Studying the zippering process during gastrulation in Cnidaria: Aligning an invaginating germ layer with the help of filopodia using 3D deformable cell based simulations
<p>This dataset contains the scripts and end results of zippering simulation experiments.<br>The data are the results of a 3D cell based model that was used to investigate zippering aided invagination: Pulling the cell sheet inwards, and uses cell-cell adhesion, filopodia, apical constriction, cell volume conservation, collision detection and handeling. </p>
BovReg_eqTL RNAseq demo input data as counts and aligned bam files
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M3: A Multi-Image Multi-Modal Entity Alignment Dataset
<p><span>M3, an MMEA benchmark equipped with multiple images retrieved from respective search engines, which better mirrors real-life challenges. We utilize the widely used DBP15K dataset as the foundational dataset, which includes three cross-ingual datasets: Chinese-English (ZH-EN), Japanese-English (JA-EN), and French-English (FR-EN).</span></p>
Multiple whole genome alignment of 63 Nymphalidae (HAL file, alignment version 1.0), plus protein-coding annotations for each of the species in the hall file.
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Dataset: Alignment Healthcare, Inc. (ALHC) Stock Performance
This dataset provides historical stock market performance data for specific companies. It enables users to analyze and understand the past trends and fluctuations in stock prices over time. This information can be utilized for various purposes such as investment analysis, financial research, and market trend forecasting.
Dataset and code for Fast sequence alignment for centromere with RaMA
<p>Dataset and code for Fast sequence alignment for centromere with RaMA</p>
Multiway Alignment of Twitter networks from 2019 and 2023 Finnish Parliamentary Elections
<p>This dataset includes partition identifiers obtained from retweet networks collected before the 2019 Finnish Parliamentary Elections and before the 2023 Finnish Parliamentary Elections from conversation streams related to Finnish political parties (SDP, National Coalition, Finns Party, Green Party, Left Party, Center Party) and salient topics (economic policy, social security, immigration, climate, education).</p> <p>The column headers in the two files are the same and indicate the topic of the retweet network. Each row in one file represents all the memberships of one particular Twitter account for the corresponding networks. Memberships are obtained by partitioning each retweet network with METIS algorithm into two similar-sized groups with minimal retweet activity between them. For each column, one partition includes all users marked with 0, whereas the other partition includes all users marked with 1. The order of the numbering is random. Missing values mean that the account was not found in the corresponding network.</p> <p>The dataset does not contain any identifying information or original raw data from the Twitter platform. Anonymization was achieved by randomly shuffling the order of the users so that, within each file, a row index identifies a user. Importantly, there no correspondence can be implied between users in 2019 and users in 2023: in general, the user at row 1 in the 2019 dataset is not the same as the user at row 1 in the 2023 dataset.</p>
Alignment and mapping methodology impact transcript abundance estimation
<pre>SRR109.txt -> list of accession numbers used for experimental analysis. simulatedquants -> Bowtie2 pipeline quantification results on the 109 samples, that are used to simulate datasets for futher analysis. scriptsSimulate -> scripts to generate simulated data using the 109 quantification results on real data. The "runme.sh" file can be executed to generate a "data" folder with all the simulated reads and ground truth count and TPM values. table1Data -> fasta and true abundance files for 10 replicates of simulated data (from human transcriptome GENCODE v29) used to generate table 1 of the manuscript. table2Data -> fasta and true abundance files for 10 replicates of simulated data (from mouse transcriptome PWK variant) used to generate table 2 of the manuscript. refFastas -> the human and mouse reference fasta files containing the sequence-similar decoy sequences, which can be used to construct the salmon index for SA.</pre>
Gutenberg Catalog Aligned with Metadata
<p>This is the gutenberg dataset enriched with VIAF and LOC IRI</p>
Aligned Cross-modal Integration and Regulatory Heterogeneity Characterization of Single-Cell Multiomic Data with Deep Contrastive Learning
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Alignment and phylogeny data for: First Record of Euwallacea fornicatus Eichoff (Coleoptera: Curculionidae: Scolytinae) in Spain
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Probabilistic Alignment of Single-Cell Data
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FORAlign: Accelerating gap-affine DNA pairwise sequence alignment using FOR-blocks based on FOur Russians approach with linear space complexity
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Dastset and code for Fast sequence alignment for centromere with RaMA
<p>Dastset and code for Fast sequence alignment for centromere with RaMA</p>
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Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.