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29,897 results for “activism”
Hanhaoyang123/Pozzolanic-activity-experimental-dataset-of-calcined-coal-gangue-v1.0.2: Pozzolanic-activity-experimental-dataset-of-calcined-coal-gangue-v1.0.2
<p>This release contains experimental data on the pozzolanic of calcined coal gangue. "The data on the strength" presents the compressive and flexural strength data of cement mortar specimens (40×40×160 cm) containing 30% calcined coal gangue at different temperatures and curing times (3 days, 7 days, and 28 days). "Column chart of strength" visually represents the flexural and compressive strength data mentioned above in the form of bar charts, with temperature intervals on the x-axis and flexural strength and compressive strength on the y-axis. "R3 activity test data" displays the weights before and after calcination, along with the weight difference representing the combined water content measured through R3 activity testing. "The bar chart of R3 activity test" visually represents the combined water content in the form of bar charts, with temperature intervals on the x-axis and combined water content on the y-axis. Thermogravimetric data show the changes in TG and DTG concerning temperature(T). FTIR curve data at different temperatures include Wavenumber and absorbance values. XRD curve data display Degrees and Intensity, along with 80 scanning electron microscope images capturing different temperature coal gangue powder photos.</p>
Synthetic automotive LiDAR with non-systematic error and automotive LiDAR based on active stereo dataset
<p>The synthetic dataset was generated by transforming the original dataset using several methods. Each of these transformations occurs from a use case:</p><ul><li>UC1 is the original dataset obtained from [1] and represents a point cloud dataset captured by an ideal LiDAR</li><li>UC2 is a realistic point cloud dataset obtained by simulating the non-systematic error of a Velodyne HDL-64E and applying to UC1</li><li>UC3 is our approach to replace the LiDAR with an active stereo setup. Where the point cloud are captured using two cameras, operating stereoscopically, and a dot projector. The cameras are perfectly calibrated and the triangulation is always correct.</li><li>UC4 also obtains the point clouds through triangulation. However we introduced a calibration error on the right camera. The error has the value of 1 pixel and is added to every dimension of the rotation matrix of the right camera.</li><li>UC5 performs an ideal triangulation, same as UC3. However, in this use case, we introduce camera noise to the point clouds.</li><li>UC6 is a combination of the triangulation from UC4 and the camera noise from UC5.</li></ul><p>Additionally, the labels, images and calibration file are also in [1]. For further details, please check the dataset generation source code [2]. </p><p>[1] https://zenodo.org/records/7184990</p><p>[2] https://github.com/RobertoGraca/Active_Stereo_Based_LiDAR</p>
Daily activity time series of ants, Camponotus japonicus
<p>Social insects often share tasks among individuals. In this study, we analyzed the foraging activity of ants (<em>Camponotus japonicus</em>) and recorded the daily passage event counts of individual workers between a nest chamber and a foraging arena using five monodomous colonies. We proposed two hypotheses on the time series of foraging frequency by individual worker ants:</p> <p>(i) Regarding the time series of foraging frequency by individual worker ants, the foraging frequency on a certain day could be expressed by the product of the foraging frequency on the previous day and the exponential of a random number.<br>(ii) The random numbers are correlated between some pairs of worker ants.</p> <p>The results for the five tested ant colonies showed that the probability of total daily passage counts (the sum of an individual's passage count) were characterized by a log-normal distribution. The worker ants behaved differently in terms of active days and foraging frequency. However, for >54% of the worker ants, the probability of the daily passage count was characterized by a log-normal distribution, and these worker ants performed >72% of the tasks in each colony. Furthermore, for >73% of the worker ants, the time development of passage count was confirmed to be mathematically modelled; the logarithmic first difference between the passage counts on a certain day and those on the previous day was a random normal variable. These results support hypothesis (i). Additionally, the random numbers, that were equivalent to the logarithmic first difference, were correlated for some pairs of worker ants. These results support hypothesis (ii).</p>
Activated Carbon Cloth Electrodes for Capacitive Deionization: A Neutron Imaging Study
<p>Neutron images of capacitive deionization by activated carbon cloths.</p><p>Corresponding readouts from potentiostat.</p><p>Nitrogen gas adsorption data of the activated carbon cloths.</p>
Contrasting Activation Characteristics of Biomass Burning and Fossil Fuel Combustion Aerosols in Fogs and Clouds: Implications for Regional Air Quality and Climate
<p>The key 'jul' in data use 2021-01-01 as the referece day, for example, 2021-01-02 12:00:00 corresponding to jul of 2.5. </p>
Dataset: The Mononuclear Metal-Binding Site of Mo-Nitrogenase Is Not Required for activity
<p>Dataset for publication: <a href="https://doi.org/10.1021/jacsau.3c00567">https://doi.org/10.1021/jacsau.3c00567</a> </p>
Reconstructing the feeding ecology of Cambrian sponge reefs: The case for active suspension feeding in Archaeocyatha
Sponge-grade Archaeocyatha were early Cambrian biomineralizing metazoans that constructed reefs globally. Despite decades of research, many facets of archaeocyath palaeobiology remain unclear, making it difficult to reconstruct the palaeoecology of Cambrian reef ecosystems. Of specific interest is how these organisms fed; previous experimental studies have suggested that archaeocyaths functioned as passive suspension feeders relying on ambient currents to transport nutrient-rich water into their central cavities. Here, we test this hypothesis using computational fluid dynamics (CFD) simulations of digital models of select archaeocyath species. Our results demonstrate that, given a range of plausible current velocities, there was very little fluid circulation through the skeleton, suggesting obligate passive suspension feeding was unlikely. Comparing our simulation data with exhalent velocities collected from extant sponges, we infer an active suspension feeding lifestyle for archaeocyaths. The combination of active suspension feeding and biomineralization in Archaeocyatha may have facilitated the creation of modern metazoan reef ecosystems.
Fig. 1 in Habitat Preferences And Activity Patterns Of The Larger Mammal Community In Phnom Prich Wildlife Sanctuary, Cambodia
Fig. 1. Locations of camera-traps within Phnom Prich Wildlife Sanctuary, eastern Cambodia.
IMBALANCED MACHINE LEARNING CLASSIFICATION MODELS FOR REMOVAL BIOSIMILAR DRUGS AND INCREASED ACTIVITY IN PATIENTS WITH RHEUMATIC DISEASES
<p>Objective: Predict long-term disease worsening and the removal of biosimilar medication in patients with rheumatic diseases.</p><p>Methodology: Observational, retrospective, and descriptive study. Review of a database of patients with immune-mediated inflammatory rheumatic diseases. Disease worsening and removing biosimilars are imbalanced variables, that require using imbalanced machine learning models selected based on their superior f1-scores and great accuracy. Previously, we selected the most important variables using mutual information tests.</p><p>Results: The best imbalanced machine learning models to predict disease worsening and the removal of the biosimilar obtained f1-scores of 0.52 and 0.63, respectively. Both models are decision trees. In the first one, two important factors are switching of biosimilar and age, and in the second, the relevant variables are optimization and the value of the initial CRP. </p><p>Conclusions: Biosimilar drugs do not always work well for rheumatic diseases. We obtained two imbalanced machine learning models to detect those cases, where the drug should be removed or where the activity of the disease increases from low to high. Our decision trees use variables, such as age or switching, not considered in previous studies.</p>
Dataset/Models for: Active learning accelerated exploration of the single atom local environments in multimetallic systems for oxygen electrocatalysis
<p>This is the datasets and trained models for the work "Active learning accelerated exploration of the single atom local environments in multimetallic systems for oxygen electrocatalysis", by Hoje Chun, Jaclyn R. Lunger, Jeung Ku Kang, Rafael Gómez-Bombarelli, and Byungchan Han. Folder named Models contains the trained models of "m-PaiNN" and "per-site PaiNN". Folder named Dataset contains the torch dataset and Dataset_raw contains the raw Density Functional Theory (DFT) dataset parsed in format of pymatgen Structure. Some structures (868) in the search space are missing due to the lost track of the geometry optimization during the initial dataset curation.</p>
Present status, future trends, and control strategies of invasive alien plants in China affected by human activities and climate change
<p>Invasive alien plants (IAPs) have serious environmental and economic impacts, especially in vulnerable areas of China. However, IAP richness distribution patterns, their driving factors, and the dynamic shifts in potential distribution areas remain elusive. We assessed IAP richness distribution patterns and drivers using 402 IAPs recorded in China at 88,926 occurrence points, and then predicted their potential distribution areas. The results show that IAP hotspots were mainly located in southeastern China, especially coastal areas of the South and East and large inland cities. Population density, gross domestic product (GDP), and four climate variables associated with precipitation and temperature jointly influenced the richness distribution pattern of all IAPs. Specifically, population density and GDP impacted the richness distribution pattern of narrow-range IAPs, and population density, GDP, distance to the nearest national highway, and five climate variables affected the richness distribution pattern of widespread IAPs. Only GDP contributed significantly to the richness distribution pattern of the top 5% hotspot grid cells, whereas population density, GDP, and precipitation in the driest month (BIO14) significantly influenced the richness distribution patterns of hotspots for both the top 10% and top 20%. Prediction analysis demonstrated that southeastern China would have a particularly high invasion risk under both current and future climate scenarios. Regions with increases in predicted species richness are more common (44.83%–64.97%) than those with decreases, except under the Representative Concentration Pathway (RCP) 4.5 scenario. Climate change will contribute greatly to the expansion of potential IAP distribution areas under both optimistic (RCP 2.5) and pessimistic scenarios (RCP 8.5). The results of this study provide insights into the priority management of IAPs through developing promising strategies for the control and prevention of IAP invasion.</p>
ScientISST MOVE: Annotated Wearable Multimodal Biosignals recorded during Everyday Life Activities in Naturalistic Environments
<p>A multi-modality, multi-activity, and multi-subject dataset of wearable biosignals.</p><p><strong>Modalities:</strong> ECG, EMG, EDA, PPG, ACC, TEMP</p><p><strong>Main Activities:</strong> Lift object, Greet people, Gesticulate while talking, Jumping, Walking, and Running</p><p><strong>Cohort: </strong>17 subjects (10 male, 7 female); median age: 24</p><p><strong>Devices: </strong>2x ScientISST Core + 1x Empatica E4</p><p><strong>Body Locations: </strong>Chest, Abdomen, Left bicep, wrist and index finger</p><p>No filter has been applied to the signals, but the correct transfer functions were applied, so the data is given in relevant unis (mV, uS, g, ºC).</p><p>For more information on background, methods and the acquisition protocol, refer to <a href="https://doi.org/10.13026/0ppk-ha30">https://doi.org/10.13026/0ppk-ha30</a>.</p><p>========</p><p>In this repository, there are two formats available:</p><h4><strong>a) LTBio's Biosignal files. Should be open like:</strong></h4><p><i>x = Biosignal.load(path)</i></p><p>LTBio Package: <a href="https://pypi.org/project/LongTermBiosignals/">https://pypi.org/project/LongTermBiosignals/</a></p><p>Under the directory <i>biosignal</i>, the following tree structure is found: <i>subject/x.biosignal</i>, where <i>subject</i> is the subject's code, and <i>x</i> is any of the following {<i> acc_chest, acc_wrist, ecg, eda, emg, ppg, temp</i> }. Each file includes the signals recorded from every sensor that acquires the modality after which the file is named, independently of the device.</p><p>Channels, activities and time intervals can be easily indexed with the index operator <i>[]</i> ( <a href="https://ltbio.readthedocs.io/en/latest/learn/basic/ltbio101.html">https://ltbio.readthedocs.io/en/latest/learn/basic/ltbio101.html</a> ).</p><p>A sneak peak of the signals can also be quickly plotted with: <i>x.preview.plot()</i></p><p>Any Biosignal can be easily converted to NumPy arrays or DataFrames, if needed.</p><h4><strong>b) CSV files. Can be open like:</strong></h4><p><i>x = pandas.read_csv(path)</i></p><p>Pandas Package: <a href="https://pypi.org/project/pandas/">https://pypi.org/project/pandas/</a></p><p>These files can be found under the directory <i>csv</i>, named as <i>subject.csv</i>, where <i>subject</i> is the subject's code. There is only one file per subject, containing their full session and all biosignal modalities. When read as tables, the time axis is in the first column, each sensor is in one of the middle columns, and the activity labels are in the last column. In each row are the samples of each sensor, if any, at each timestamp. At any given timestamp, if there is no sample for a sensor, it means the acquisition was interrupted for that sensor, which happens between activities, and sometimes for short periods during the running activity. Also in each row, on the last column, is one or more activity labels, if an activity was taking place at that timestamp. If there are multiple annotations, the labels are separated by vertical bars (e.g '<i>run | sprint</i>'). If there are no annotations, the column is empty for that timestamp.</p><p>In order to provide a tabular format with sensors with different sampling frequencies, the sensors with sampling frequency lower than 500 Hz were upsampled to 500 Hz. This way, the tables are regularly sampled, i.e., there is a row every 2 ms. If a sensor was not acquiring at a given timestamp, the corresponding cell with be empty. So, not only the segments with samples are regularly sampled, but the interruptions are also discretised. This means that if, after an interruption, a sensor starts acquiring at a non regular timestamp, the first sample will be written on the previous or the following timestamp, by half-up rounding. Naturally, this process cumulatively introduces lags in the table, some of which cancel out. Each individual lag is no longer than half the sampling period (1 ms), hence negligible. The cumulative lags are no longer than 48 ms for all subjects, which is also negligible. Nevertheless, only the LBio's Biosignal format preserves the exact original timestamps (10E-6 precision) of all samples and the original sampling frequencies.</p><p>================</p><p>Both include annotations of the activities, however LTBio bio signal files have better time resolution and include clinical data and demographic data as well.</p>
Data from: Reactive high-spin iron(IV)-oxo sites through dioxygen activation in a metal–organic framework
<p>In nature, nonheme iron-containing enzymes use dioxygen to generate high-spin iron(IV)=O species for a variety of oxygenation reactions. Although scientists have long sought to mimic this reactivity, the enzyme-like activation of dioxygen to form high-spin iron(IV)=O species remains an unrealized goal in synthetic chemistry. Here, we report a metal–organic framework featuring iron(II) sites with a local structure similar to that in α-ketoglutarate-dependent dioxygenases. The framework reacts with dioxygen at low temperatures to form high-spin iron(IV)=O species that are characterized using in situ diffuse reflectance infrared Fourier transform, in situ and variable-field Mössbauer, Fe Kβ x-ray emission, and nuclear resonance vibrational spectroscopies. In the presence of dioxygen, the framework is competent for catalytic oxygenation of cyclohexane and the stoichiometric conversion of ethane to ethanol.</p>
Data for "Statistical characteristics of thunderstorm activity in the middle reaches of the Yangtze River Basin based on a five-year cloud-to-ground lighting dataset"
<p>Data for "Statistical characteristics of thunderstorm activity in the middle reaches of the Yangtze River Basin based on a five-year"</p>
Dataset for: "Gas buffering of magma chamber contraction during persistent explosive activity at Mt. Etna volcano"
<p>Data used for generating the figures in the paper "Gas buffering of magma chamber contraction during persistent explosive activity at Mt. Etna volcano", accepted for publication in Nature Communications Earth & Environment.</p>
Oxygen consumption (VO 2) was determined from the formula in Diurnal activity, temperature responses and endothermy in three South American cicadas (Homoptera: Cicadidae: Dorisiana bonaerensis, Quesada gigas and Fidicina mannifera)
Oxygen consumption (VO 2) was determined from the formula
Data to our paper "Water-soluble ionic carbon nitride as unconventional stabilizer for highly catalytically active ultrafine gold nanoparticles"
<p>Data to our paper "Water-soluble ionic carbon nitride as unconventional stabilizer for highly catalytically active ultrafine gold nanoparticles"</p>
Molecular dynamics trajectories, GROMACS input files, and analysis code from "Rational optimization of a transcription factor activation domain inhibitor" by Basu et. al, Nature Structural & Molecular Biology, 2023
<p>Molecular dynamics trajectories, GROMACS input files, and analysis code from "Rational optimization of a transcription factor activation domain inhibitor" by Basu et. al, Nature Structural & Molecular Biology, 2023</p> <p> </p> <p> </p>
Reception of a physical activity intervention program in German older adults. Data from a feedback analysis of PROMOTE II.
<p>As part of the<strong> AEQUIPA </strong>prevention research network, the aim of the <strong>PROMOTE II</strong> study was to gain insights into primary prevention for healthy aging. One focus was on the development and dissemination of ready-to-use tools and work aids to promote physical activity.</p><p>As part of a nine-month randomized trial with a cross-over design among adults aged 60 and above, eligible participants from 14 districts in Bremen in proximity to the two study centers (one in the North and one in the East of the city of Bremen, Germany) were randomly assigned to either a) a print-based intervention (PRINT) or b) a web-based intervention (WEB). Randomly selected thirty percent of the web-based intervention group received an activity tracker in addition (WEB+).</p><p>Usage of program components, attendance of group sessions and acceptance of the intervention were assessed via self-administered paper-based questionnaires three and nine months after baseline as well as feedback interviews and class recordings. Participant feedback was analyzed using quantitative methods on a descriptive basis, as well as using qualitative content analysis of open-ended questions, group-interviews and protocols based on the socio-ecological model as coding framework.</p><p>This publication provides the coding matrix, including the participant feedback data.</p>
Catalytic activity of [Mim][OTf]-TiO2 catalyst - NCN project OPUS, grant no. 2020/37/B/ST8/00693.
<p>Dataset contains results obtained during the NCN project OPUS, grant no. 2020/37/B/ST8/00693. The file presents the catalytic activity of [Mim][OTf]-TiO2, [Mim][OTf] and TiO2 catalysts in the esterification of oleic acid and 2-ethylhexanol.</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.