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849 results for “linear”
Heatwave breaks down the linearity between sun-induced fluorescence and gross primary production. Reproducible workflow
<p>Dataset for manuscript entitled "Heatwave breaks down the linearity between sun-induced fluorescence and gross primary production" accepted for publication in New Phytologist. The dataset was obtained for the site Majadas del Tietar, Spain, between June/2018 and August/2018. It consists of eddy covariance data, sun-induced fluorescence data and active fluorescence data. </p>
Global Soil Moisture-Air Temperature Interactions from Linear and Nonlinear Granger Causalities
<p>These datasets were generated to assess linear and nonlinear Granger causalities in the submitted manuscript, Global Soil Moisture-Air Temperature Interactions from Linear and Nonlinear Granger Causalities by Bhatti et al. submitted to AGU-GRL. Nonlinear GC here is achieved with the Kernel Granger causality by Marinazzo et al. (2008). The data was used to develop theoretical experiments that help validate the strengths and limitations of both the linear Granger causality and the Kernel Granger causality before applying to real world datasets</p>
Incorporating effects of age on energy dynamics predicts non-linear maternal allocation patterns in iteroparous animals
<p>Iteroparous parents face a trade-off between allocating current resources to reproduction versus maximizing survival to produce further offspring. Optimal allocation varies across age, and follows a hump-shaped pattern across diverse taxa, including mammals, birds and invertebrates. This non-linear allocation pattern lacks a general theoretical explanation, potentially because most studies focus on offspring number rather than quality and do not incorporate uncertainty or age-dependence in energy intake or costs. Here, we develop a life history model of maternal allocation in iteroparous animals. We identify the optimal allocation strategy in response to stochasticity when energetic costs, feeding success, energy intake, and environmentally-driven mortality risk are age-dependent. As a case study, we use tsetse, a viviparous insect that produces one offspring per reproductive attempt and relies on an uncertain food supply of vertebrate blood. Diverse scenarios generate a hump-shaped allocation: when energetic costs and energy intake increase with age; and also when energy intake decreases, and energetic costs increase or decrease. Feeding success and mortality risk have little influence on age-dependence in allocation. We conclude that ubiquitous evidence for age-dependence in these influential traits can explain the prevalence of non-linear maternal allocation across diverse taxonomic groups.</p>
A new ChEMBL dataset for FastTargetPred and target fishing for an exhaustive list of linear tetrapeptides
<p>A ChEMBL-v29 dataset was generated to be used with the ligand-based similarity search target prediction engine FastTargetPred (https://github.com/ludovicchaput/FastTargetPred). Using this new dataset, attempts to predict macromolecular targets for a published dataset of 160,000 tetrapeptides was performed.</p> <p>The dbchembl29 directory contains all the files for FastTargetPred. This command line tool compares using different types of fingerprints, a file containing small query molecules in SDF format (it can be 1 molecule or a collection) to molecules extracted from ChEMBL29. If a match is found, this suggests that your query molecule is similar to a ChEMBL compound and as the ChEMBL compound has bioactivity data against one or more macromolecular target, then this suggests that your query compound could bind to targets that interact with compounds that are similar to the query molecule. The so-called similarity principle in chemistry. Fingerprints are computed with http://www.mayachemtools.org/, a collection of Perl and Python scripts for Chemoinformatics and (Structural) Bioinformatics.</p> <p>To run FastTargetPred with the new ChEMBL 29 data, you just need to unzip the dbchembl29 directory into the FastTargetPred main directory.</p> <p>The default FastTargetPred commands (e.g., python3 FastTargetPred.py rivaroxaban.sdf, the default command uses ECFP4 fingerprints and a Tanimoto coef of 0.6, rivaroxaban here is the query compound, it is provided in the extra_data directory) will use the data present in the default db directory and thus a curated version of ChEMBL-25 release. It was the version of the ChEMBL database available when FastTargetPred was developed. Since then, many new molecules have been added and this is why we generated the ChEMBL-29 dataset (last ChEMBL version at the time of writing).</p> <p>To use the new ChEMBL-29 data, you can run the following command:</p> <p>python3 FastTargetPred.py rivaroxaban.sdf -fp MACCS -tc 0.9 -db dbchembl29/chembl29_active</p> <p>This applies a similarity search for the query compound (here rivaroxaban, you can for instance move this SDF file in the directory containing the file FastTargetPred.py) using MACCS fingerprints, a Tanimoto coefficient threshold of 0.9 and the -db option forces the system to look at the ChEMBL29 curated data and not the default ChEMBL-25 data. This 0.9 value means to focus on molecules very similar to rivaroxaban present in the ChEMBL data. If one is looking for more distantly related compounds, then a value of 0.7 can be used. Users can try different values or try consensus scoring...See FastTargetPred: a program enabling the fast prediction of putative protein targets for input chemical databases. Chaput et al., Bioinformatics. 2020 Aug 15;36(14):4225-4226</p> <p>The chembl29 directory also contains 714,780 compounds (canonical SMILES strings) extracted from ChEMBL29 that have bioactivity data. Fingerprints could not be computed for 19 molecules that have unusual chemistry. We selected the following thresholds (eg, binding assays, activity against targets less than 20 micro-molar, ChEMBL confidence_score = 6 or above, maximum = 9).</p> <p>With this new dataset, we attempted to predict potential targets with FastTargetPred for 160,000 input query peptides (4 amino acids, combination should be 20 x 20 x 20 x 20) previously reported by Dewi Prasasty and Perdana Istyastono, Data in brief 27 (2019) 104607. The peptides for which a putative target was predicted are shown in two DataWarrior files with the amino acid sequence of the query peptide, the compounds found to be similar in the ChEMBL29 dataset (fingerprints = ECFP4, Tanimoto 0.6) and thus the compound IDs, the target ChEMBL IDs, mapping to the UniProt database when available, information about disease involvements, Reactome pathway database identifiers. These two DataWarrior files are searchable, can be sorted and hyperlinks to the ChEMBL, UniProt and Reactome databases have been inserted.</p> <p> </p>
Linear Kinematic Feature detected and tracked in sea-ice deformation simulationed by all models participating in the Sea Ice Rheology Experiment and from RGPS
<p>Linear Kinematic Features (LKFs) detected and tracked in sea-ice deformation fields simulated by sea-ice models participating in the Sea Ice Rheology Experiment (SIREx), a model intercomparison project of the Forum of Arctic Modeling and Observational Synthesis (FAMOS). These data are the basis of the feature-based evaluation of sea-ice deformation in Hutter et al., Sea Ice Rheology Experiment (SIREx), Part II: Evaluating linear kinematic features in high-resolution sea-ice simulations, Journal of Geophysical Research: Oceans (2022). This paper also provides further details on the parameters of the LKF extraction.</p> <p>The LKF data sets in this archive are stored in a csv-files for each year (1997 and/or 2008), which use semi-colons as delimiters. Each row corresponds to a pixel that was identified as LKF and the following information for this pixels is stored: Start Year, Start Month, Start Day, End Year, End Month, End Day, LKF No., Parent LKF No., lon, lat, ind_x, ind_y, divergence rate, shear rate. All pixels belonging to the same LKF have the same LKF number. Tracked LKFs are linked by the parent LKF number, where "0" denotes LKFs that newly formed. Detailed information on all variables is provided in the additional notes.</p>
Linear rheology of liquid foam - data from "Delayed elastic contributions to the viscoelastic response of foams"
<p>Linear rheological data of Gillette shaving cream "normal skin" made by Gillette UK LTD, acquired at the Department of Physics, University of Fribourg, Switzerland, between 2019 and 2022. Dataset contains elastic modulus, creep-recovery, stress relaxation, and frequency sweep experimental data, together with model data, as described in "Delayed elastic contributions to the viscoelastic response of foams", The Journal of Chemical Physics, 2022, published in the special issue <em>Slow Dynamics</em> [DOI: 10.1063/5.0085773].</p>
Fig. 2 in Linear Transect Surveys Of Abundance And Density Of Cetaceans In The Area Near The Dzharylgach Island In The North-Western Black Sea
Fig. 2. Linear transect survey of cetaceans near the Dzharylgach Island in 2017 (lt, linear transect survey encounters; vis, additional visual observations).
Fig. 1 in Linear Transect Surveys Of Abundance And Density Of Cetaceans In The Area Near The Dzharylgach Island In The North-Western Black Sea
Fig. 1. Linear transect survey of cetaceans near the Dzharylgach Island in 2016 (lt, linear transect survey encounters; vis, additional visual observations).
A comparison of the World Health Organisation's HEAT model results using a non-linear physical activity dose response function with results from the existing tool
<p>Datasets relating to the Wellcome Open Research publication of the same name.</p>
Gravity waves in Titan's atmosphere: A comparison between linearized wave model calculations and HASI observations
<p>The data for the article "Gravity waves in Titan's atmosphere: A comparison between linearized wave model calculations and HASI observations" (GWTA). </p> <p> </p> <ol> <li>"Titan_CJP_std_chem.dat" is the background atmosphere data of Titan's atmosphere from Strobel's model. It is used in Figure 1 of the article.</li> <li>"HASI_T_p_rho_vsZ_2008.dat" is the data for Cassini-Huygens observations in Titan's atmosphere. It is used in Figure 1 of the article.</li> <li>"Mma-Program-for-GW-on-Titan.txt" is the main Mathematica program to simulate the gravity waves on Titan.</li> <li>"solutions-fun.rar" is the simulation result. This RAR file includes 174 gravity wave samples simulated with different periods and horizontal wavelengths (can be read from the subfile names after uncompressing). These gravity wave solutions are stored as InterpolatingFunction of Mathematica. The solution describes the gravity wave temperature, velocity, and density perturbations profiles from altitude 300km to 2000km. However, they are plain texts and can easily be read by any software. Figures from 2-10 are based on these data.</li> </ol> <p> </p>
Supplementary data and files to Figure 9 of Eva Rosenstock, Linear Pottery and Harris (2022)
<p>Supplements to the printed version of Figure 9 in: Eva Rosenstock, Linear Pottery and Harris: A Case Study in the Spatio-temporal Logic of Archaeological Sites. In: Elke Kaiser - Michael Meyer - Silviane Scharl - Stefan Suhrbier (Hrsg.), Wissensschichten. Festschrift für Wolfram Schier zu seinem 65. Geburtstag. Studia Honoraria (Rahden/Westf. 2022) 179-198.</p> <p>HMC matrix based on Figure 8 but also considering ceramic CA information for further layer attributions, based on the data published in Claus.-Joachim Kind, Ulm-Eggingen. Die Ausgrabungen 1982 bis 1985 in der bandkeramischen Siedlung und der mittelalterlichen Wüstung (Stuttgart 1989).</p> <p>Full collapsed and uncollapsed versions in CSV, Graph Markup Language (compatible with e.g. yEd freeware <a href="https://www.yworks.com/products/yed">https://www.yworks.com/products/yed</a>) and HMCX (compatible with Harris Matrix Composer <a href="https://harrismatrixcomposer.com/#/">https://harrismatrixcomposer.com/#/</a>), and jpeg.</p>
Supplementary data and files to Figure 8 of Eva Rosenstock, Linear Pottery and Harris (2022)
<p>Supplements to the printed version of Figure 8 in: Eva Rosenstock, Bandkeramik and Harris: a case study in the spatio-temporal logic of archaeological sites. In: Elke Kaiser - Michael Meyer - Silviane Scharl - Stefan Suhrbier (Hrsg.), Wissensschichten. Festschrift für Wolfram Schier zu seinem 65. Geburtstag. Studia Honoraria (Rahden/Westf. 2022) 179-198.</p> <p>HMC matrix based on an alternative model for Ulm-Eggingen along stratigraphic observations and spatial relationships between postholes, fences, buildings, and corresponding longitudinal pits, based on the data published in C.-J. Kind, Ulm-Eggingen. Die Ausgrabungen 1982 bis 1985 in der bandkeramischen Siedlung und der mittelalterlichen Wüstung (Stuttgart 1989).</p> <p>Full collapsed and uncollapsed versions in CSV, Graph Markup Language (compatible with e.g. yEd freeware <a href="https://www.yworks.com/products/yed">https://www.yworks.com/products/yed</a>) and HMCX (compatible with Harris Matrix Composer <a href="https://harrismatrixcomposer.com/#/">https://harrismatrixcomposer.com/#/</a>), and jpeg.</p>
Supplementary data and files to Figure 7 of Eva Rosenstock, Linear Pottery and Harris (2022)
<p>Supplements to the printed version of Figure 7 in: Eva Rosenstock, Bandkeramik and Harris: a case study in the spatio-temporal logic of archaeological sites. In: Elke Kaiser - Michael Meyer - Silviane Scharl - Stefan Suhrbier (Hrsg.), Wissensschichten. Festschrift für Wolfram Schier zu seinem 65. Geburtstag. Studia Honoraria (Rahden/Westf. 2022) 179-198.</p> <p>HMC matrix rendering of the spatio-temporal model for Ulm-Eggingen according to the yard model analysis by C.-J. Kind, Ulm-Eggingen. Die Ausgrabungen 1982 bis 1985 in der bandkeramischen Siedlung und der mittelalterlichen Wüstung (Stuttgart 1989).</p> <p>Full collapsed and uncollapsed versions in CSV, Graph Markup Language (compatible with e.g. yEd freeware <a href="https://www.yworks.com/products/yed">https://www.yworks.com/products/yed</a>) and HMCX (compatible with Harris Matrix Composer <a href="https://harrismatrixcomposer.com/#/">https://harrismatrixcomposer.com/#/</a>), and jpeg.</p>
A Method for Generating a Quasi-Linear Convective System Suitable for Observing System Simulation Experiments: Dataset
<p>This repository provides data files to quickly run the QLCS observing system simulation experiments. The data file includes assimilated observations prepared for the data assimilation research testbed system (./data/obs/). The file also contains a restart files to initialize the nature run simulation (./data/nature_run/) and the initial prior ensemble at the time of the first data assimilation cycle (./data/initial_fcst_ensemble/).</p>
Text-fig. 4: Pterigophycos sp., details of specimen in Text-fig. 3a. a: Blades B5–7; b: Close-up of (a), focusing on attachment of small blades B5–7 to holdfast structure; c: Detail of holdfast with several linear elements extending from proximal portion; d: Detail of blade B2, showing midrib and spathulate lamina segments; e: Detail of blade B1, showing lowermost, smallest lamina segments; f: tiny bivalve shell on stipe of blade B1, scale bar = 5 mm; g: Detail of blade B2, showing proximal beginning of lamina segmentation. Scale bars = 1 cm unless otherwise stated. in A Whole-Plant Specimen Of The Marine Macroalga Pterigophycos From The Eocene Of Bolca (Veneto, N-Italy)
Text-fig. 4: Pterigophycos sp., details of specimen in Text-fig. 3a. a: Blades B5–7; b: Close-up of (a), focusing on attachment of small blades B5–7 to holdfast structure; c: Detail of holdfast with several linear elements extending from proximal portion; d: Detail of blade B2, showing midrib and spathulate lamina segments; e: Detail of blade B1, showing lowermost, smallest lamina segments; f: tiny bivalve shell on stipe of blade B1, scale bar = 5 mm; g: Detail of blade B2, showing proximal beginning of lamina segmentation. Scale bars = 1 cm unless otherwise stated.
data sets of "Dynamic Linear Modeling estimates of long-term ozone trends from homogenized Dobson Umkehr profiles at Arosa, Switzerland"
<p>data sets from "Dynamic Linear Modeling estimates of long-term ozone trends from homogenized Dobson Umkehr profiles at Arosa, Switzerland"</p> <p>Monthly means ozone profiles data sets of MCH homogenized Dobson D051 and of Brewer B040 used in the article entitled: "Dynamic Linear Modeling estimates of long-term ozone trends from homogenized Dobson Umkehr profiles at Arosa, Switzerland" by Eliane Maillard Barras, Alexander Haefele, René Stübi, Achille Jouberton, Herbert Schill, Irina Petropavlovskikh, Koji Miyagawa, Martin Stanek, and Lucien Froidevaux.</p> <p><a href="https://doi.org/10.5194/acp-2022-344">https://doi.org/10.5194/acp-2022-344</a></p>
Advantages of a synchrotron light source for fluorescence-detected linear dichroism
<p>Fluorescence-detected linear dichroism (FD-LD) enables one to collect linear dichroism spectra for oriented fluorophores in the presence of other absorbing species and light scattering. The experiment proceeds by scanning the excitation wavelength and using a filter to collect only emitted photons from the fluorophore. Thus, it has the potential to give data with enhanced selectivity and quality. By using a synchrotron radiation light source and fluorescence-detection we show data for a range of fluorophores in different orienting environments. Film and flow-oriented FD-LD spectra were collected down to 170 nm. Even for flow-oriented liposomes we have data collected down to 210 nm. For strongly scattering samples, e.g. liposomes, FD-LD has the clear advantage that scattering is absent for the longer wavelength fluorescence photons. The collimated and smaller beam size of the synchrotron radiation also give rise to sharper and more well-defined features in the spectra. </p> <p>The data here are those presented as figures in a paper submitted to the journal "Chirality" in January 2024. </p> <p>Data units are nm for the wavelength (x-axes) and the units of the LD, FD-LD and fluorescence data are described in detail in the Materials and Methods section of the associated publication. A reference to the data origin file on the Aarhus University servers is found in cell A1 of each sheet.</p>
Рис. 5. АналиЗ линейной коррелЯции параметров макробентоса от доминируюЩей фракции в пробе грунта (А, Б) и глубины (В, Г). Fig. 5. Analysis of the linear correlation of macrobenthos parameters with the dominant fraction in the bottom sample (А, Б) and depth (В, Г). in Species composition and distribution of bivalve mollusks in plankton and benthos in Nevelsky Strait in summer
Рис. 5. АналиЗ линейной коррелЯции параметров макробентоса от доминируюЩей фракции в пробе грунта (А, Б) и глубины (В, Г). Fig. 5. Analysis of the linear correlation of macrobenthos parameters with the dominant fraction in the bottom sample (А, Б) and depth (В, Г).
Data from: Determining critical periods for thermal acclimatisation using a Distributed Lag Non-linear Modelling approach
<p>Rapid changes in thermal environments are threatening many species worldwide. Thermal acclimatisation processes may partially buffer species from the impacts of these changes, but currently the knowledge about the temporal dynamics of acclimatisation remains limited. Acclimatisation phenotypes are typically determined in laboratory conditions that lack the variability and stochasticity that characterize the natural environment. Through a Distributed Lag Non-linear Model (DLNM), we use field data to assess how the timing and magnitude of past thermal exposures influence thermal tolerance. We apply the model to two Scottish freshwater Ephemeroptera species living in natural thermal conditions. Model results provide evidence that rapid heat hardening effects are dramatic and reflect high rates of change in temperatures experienced over recent hours to days. In contrast, temperature change magnitude impacted acclimatisation over the course of weeks but had no impact on short term responses. Our results also indicate that individuals may de-acclimatise their heat tolerance in response to cooler environments. Based on the novel insights provided by this powerful modelling approach, we recommend its wider uptake among thermal physiologists to facilitate more nuanced insights in natural contexts, with the additional benefit of providing evidence needed to improve the design of laboratory experiments. </p>
Dataset containing spectra of degree of linear polarization of human skin
<p>Dataset contains spectra of degree of linear polarization (DOLP) of human finger skin. Experimental studies involved 32 conditionally healthy volunteers (9 males and 23 females, aged 22-76 years).</p>
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
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.