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914 results for “filter”
Filtered chlorophyll a time series for Beaverdam Reservoir, Carvins Cove Reservoir, Claytor Lake, Falling Creek Reservoir, Gatewood Reservoir, Smith Mountain Lake, Spring Hollow Reservoir in southwestern Virginia, and Lake Sunapee in Sunapee, New Hampshire, USA during 2014-2025
Water column chlorophyll a was analyzed from 2014 to 2025 in seven freshwater reservoirs in southwestern Virginia (VA), USA, and one freshwater lake in central New Hampshire (NH), USA. These waterbodies are: Beaverdam Reservoir (Vinton, VA), Carvins Cove Reservoir (Roanoke, VA), Claytor Lake (Pulaski, VA), Falling Creek Reservoir (Vinton, VA), Gatewood Reservoir (Pulaski, VA), Smith Mountain Lake (Bedford, VA), Spring Hollow Reservoir (Salem, VA), and Lake Sunapee (Sunapee, NH). Beaverdam, Carvins Cove, Falling Creek, and Spring Hollow Reservoirs are owned and operated by the Western Virginia Water Authority as primary or secondary drinking water sources for Roanoke, Virginia; Gatewood Reservoir is a drinking water source for the Town of Pulaski, Virginia; and Smith Mountain Lake is jointly treated by the Bedford Regional Water Authority and the Western Virginia Water Authority as a drinking water source for Franklin County, Virginia. Claytor Lake is managed for hydroelectric power generation by the Appalachian Power Company. Lake Sunapee is a glacially-formed lake known for its oligotrophic water quality. The dataset consists of depth profiles of chlorophyll a samples generally measured at the deepest site of each reservoir adjacent to the dam or at the buoy site of Lake Sunapee. The water column samples were collected approximately fortnightly from March-April and weekly from May-October from 2014 - present at Falling Creek Reservoir and Beaverdam Reservoir, approximately fortnightly from May-August in most years at Carvins Cove Reservoir, approximately fortnightly from May-August in Gatewood and Spring Hollow Reservoirs from 2014-2016, approximately fortnightly from May-August of 2014 in Smith Mountain Lake, sporadically from May-August of 2014 in Claytor Lake, and sporadically from June-August of 2021-2022 and 2024-2025 in Lake Sunapee. From 2018-2025, samples were collected primarily at a single depth in each reservoir, with sample collection at two depths in F
Fern Understory as an Ecological Filter at Harvard Forest 1993-1995
We investigated the role of the fern understory as an ecological filter that influences the organization of the tree seedling bank in New England deciduous forests. The data files below summarize a series of field experiments conducted from 1993 to 1995 evaluating the response of seed germination and seedling growth and survival to experimental understory manipulation. These field studies involved three experimental manipulations of the fern understory: 1) removal of ferns 2) ferns tied back (to remove above-ground shading) 3) ferns left intact (control). These manipulations were established in 180 - 1m2 plots spanning six field sites and 2 different fern species (3 understory manipulations x 2 understory fern species x 6 sites x 5 replicates/site = 180 experimental plots).
Extended Kalman filters for close-range navigation to noncooperative targets
<p>The data sets provided here are associated to the paper “Extended Kalman filters for close-range navigation to noncooperative targets” available at this <a name="_Hlk36545040"></a><a href="https://doi.org/10.1016/j.asr.2023.10.038"><span>link</span></a>. These allow recreating the simulations discussed in Sections 5.2 – for the results plotted in Figure 7 – 5.3 (Figures 9-10), and 5.4 (Figures 11-12).</p> <p>That paper presents a set of dynamic filters for estimating the relative roto-translational state and the main parameters of a noncooperative target from an observing chaser satellite during close proximity operations. The proposed different options address a wide range of design possibilities for the architecture of the relative navigation system. All filters are derived from a common, general, core shaped as a dynamic multiplicative extended Kalman filter using dual quaternions. This allows exploiting the advantages of handling the pose (i.e., attitude and position) in a multiplicative fashion, while improving the accuracy in the estimation of the angular and linear relative velocities, as well as enabling the estimation of some meaningful parameters of the target spacecraft (e.g., the ratios of the moments of inertia, position and orientation of the principal axes frame). Moreover, by adopting relative kinematics and dynamics equations in dual quaternions, the inherent coupling of the six degrees-of-freedom motion is addressed with no approximations.</p> <p>All filters take as observations only the noisy pose measurements from an electro-optical device. For each proposed formulation, numerical simulations are carried out to show the behaviour of the filter within a scenario representative of close-range target inspection at conclusion of the mid-range rendezvous.</p>
DisVis-based filtering of contacts from co-evolution data (or other sources)
<p>Dataset described in the manuscript: <em>Improving the Quality of Co-evolution Intermolecular Contact Prediction with DisVis</em>Siri Camee van Keulen, Alexandre M.J.J. Bonvin</p> <p>Details about the data set can be found at: https://github.com/haddocking/contact-filtering</p> <p>This archive contains in addition all the models generated with HADDOCK.</p>
Data for "PTP Over Wide Area Networks With Offset Measurement Outlier Filtering"
<p>Dataset used in the manuscript "PTP Over Wide Area Networks With Offset Measurement Outlier Filtering". This dataset contains synchronization accuracy measurements over long distance links using both NTP and PTP, as well as synthetically generated PTP replays used for offline testing.</p> <p>A detailed description of the contents is found in the <code>README.md</code> file at the root of the dataset.</p>
Data: Weak Cation Selectivity in HCN Channels Results from K+-mediated release of Na+ from selectivity filter binding sites
<p>Complementary data for the paper: Weak Cation Selectivity in HCN Channels Results from K+-mediated release of Na+ from selectivity filter binding sites.</p>
Filtered AMR Graphs Bank
<p>The filtered AMR graphs bank is the output of the <a href="http://github.com/polifonia-project/Polifonia-Knowledge-Extractor">Polifonia Knowledge Extractor</a> pipeline.</p> <p>The Polifonia Mini Textual Corpus is pre-processed through coreference resolution and minimal rule-based post-OCR correction, then it is given as input to <a href="https://github.com/SapienzaNLP/spring">SPRING</a> to obtain AMR graphs.</p> <p>The filtered AMR graphs bank encompasses the sentence-AMR graph pairs extrapolated from our initial AMR graphs bank corresponding to AMR2Text-generated sentences associated with a positive (>0) <a href="https://github.com/google-research/bleurt">BLEURT</a> score.</p> <p>Full description at: <a href="https://github.com/polifonia-project/Polifonia-Knowledge-Extractor">https://github.com/polifonia-project/Polifonia-Knowledge-Extractor</a></p>
Performance Criteria and Example Parameter Sets Comparing Different Variants of the Ensemble Kalman Filter as Applied to Volcanology
<p>This dataset contains the results of various Ensemble Kalman Filter (EnKF) inversions in which synthetic GNSS and InSAR observations from an inflating magma system are assimilated into numerical models of rock deformation around a pressurized ellipsoidal magma reservoir. Each inversion uses a different variant of the EnKF, with changes to workflow meta-parameters such as the number of ensemble members or the particular update algorithm used. In particular, each filter variant is evaluated by comparing the final output model to the original synthetic model. The specific performance criteria used include (1) the root mean square error (RMSE) between the model predictions and the assimilated observations, as well as normalized misfit terms measuring the filter's ability to resolve (2) reservoir wall tensile stress, (3) easily-observable unique parameters such as reservoir position and aspect ratio, and (4) difficult-to-derive non-unique parameters such as the specific size and internal pressure of the reservoir. The assimilated data include two different scenarios, one in which inflation is caused by pressurization and another in which it is driven by a lateral reservoir expansion. Both datasets are tested with each EnKF variant. Finally, we include example matrices from within an EnKF update step to demonstrate inter-parameter correlations that develop during the assimilation and how they can be mitigated through randomization.</p>
Results of "Ensemble Kalman Filter for the Thermosphere Ionosphere", CHAMP neutral density assimilation into CTIPe for March 20, 2007
<p>These data are the result of assimilating neutral density measurements from the CHAMP satellite on March 20, 2007 into the CTIPe model and and comparison of results with observations made by the GRACE satellite. Data assimilation is performed in three configurations: Configuration (i) is ds, state correction. Configuration (ii) is dfds, both input estimatation and state correction. Configuration (iii) is df, estimation of model inputs only.</p> <p>This data is associated with the following publication:</p> <blockquote> <p>Codrescu S., M.V. Codrescu, and M. Fedrizzi (2018), An Ensemble Kalman Filter for the Thermosphere-Ionosphere, Space Weather, 16, doi:<a href="http://dx.doi.org/10.1002/2017SW001752" title="Link to external resource: 10.1002/2017SW001752">10.1002/2017SW001752</a>.</p> </blockquote> <p> </p>
Parker Solar Probe Filtered Ion Scale Wave Activity for Encounters 8 to 16
<p>The following datasets are the result of filtering algorithm applied to a wave analysis of Parker Solar Probe data from Encounters 8 to 16. The wave analysis was conducted by Kristoff Paulson using a Short-Time Fourier Transform (STFT) approach based on polarization techniques derived by Means, 1972 (DOI: <a href="http://doi.org/10.1029/JA077i028p05551">10.1029/JA077i028p055511135</a>). Included is a jupyter notebook containing the filtering algorithm, the results of the filtering, and a demonstration of how to best open the files. The dataset for each encounter contains 9 columns that correspond with:</p> <ol> <li>Date in CDF epoch</li> <li>Left-handed (LH) Integrated Wave Power (nT^2) where integration is over frequency space (0-32 Hz) of filtered activity</li> <li>Right-handed (RH) Integrated Wave Power (nT^2)</li> <li>LH median ellipticity where median is over frequency space</li> <li>RH median ellipticity</li> <li>LH median coherency</li> <li>RH median coherency</li> <li>LH median wave normal angle (deg)</li> <li>RH median wave normal angle (deg)</li> </ol> <p>In all cases, ellipticity is measured in the Parker Solar Probe spacecraft frame. Ellipticity measures the ellipticity of the polarization ellipse and takes on values between -1 and 1. Values of 1 correspond with RH circular polarization and -1 with LH circular polarization. Coherency takes on values between 0 and 1. It measures how interrelated fluctuations are where 0 represents noise and 1 represents coherent fluctuations. The wave normal angle is the angle between the wave vector, k, and the local mean magnetic field, B. Since there are inherent ambiguities in the direction of the wave vector for single spacecraft measurements, the wave normal angle is calculated such that it takes on angles from 0 to 90 degrees. The filtering algorithm selects activity in which coherency is above 0.8, absolute value of ellipticity is above 0.5, and wave normal angle is below 45 degrees such that coherent, circularly polarized, near parallel propagating wave activity on ion scales is selected. <strong>If wave power for a given time has value of 0.0, then no fluctuations in the magnetic field data passed the required filters at that time.</strong></p> <p>:</p>
Equatorial wave filtering during May-September 2020 in the ECMWF OSE experiments with and without Aeolus data
<p>These are files with the global analyses produced by the observing system experiment with and without Aeolus data, and decomposed using the MODES software. Every file contain the zonal and meridional wind components and the pseudo-geopotential. Note that the paper makes use of the zonal winds only. Files including "hel1" in their titles belong to the OSE without Aeolus winds whereas the files with "hel4" in their names are from OSE including Aeolus winds. </p> <p>File names starting with KW belong to the Kelvin waves, file names starting with All contain the total fields, IGMRG denoted the non-Rossby modes whereas Rot belongs to file names containing only the signal associated with the Rossby modes. The Kelvin wave analyses are updated for the period from 1 May to 30 September, whereas other files are available for the periods discussed in the paper.</p> <p>The two movies are named MODES_KW_May2Sep2020.gif and MODES_BalancedUwind_May2Sep2020.gif for the Kelvin and balanced (Rossby modes) zonal winds averaged within 15 degrees N and 15 degrees S, respectively. Individual figures which constitute the movies are available at https://modes.cen.uni-hamburg.de.</p> <p> </p> <p> </p>
Information Filtering in Electronic Networks of Practice: An fMRI Investigation of Expectation [Dis]confirmation
Open the record for dataset details and reuse information.
Phylogenomics of manakins (Aves: Pipridae) using alternative locus filtering strategies based on informativeness
<p>Data used in phylogenomic analyses of manakin birds. </p> <p>Datasets number 1 to 7 include sequence alignments for each locus analyzed, and datasets 4 to 7 also contain gene trees used as input for ASTRAL.</p>
New Generation UV-A Filters: Understanding Their Photodynamics on a Human Skin Mimic
<p>The sparsity of efficient commercial ultraviolet-A (UV-A) filters is a major challenge towards developing effective broadband sunscreens with minimal human- and eco-toxicity. To combat this, we have designed a new class of Meldrum-based phenolic UV-A filters. We explore the ultrafast photodynamics of coumaryl Meldrum, CMe, and sinapyl Meldrum, SMe, both in an industry standard emollient and on a synthetic skin mimic, using femtosecond transient electronic and vibrational absorption spectroscopies, and computational simulations. Upon photoexcitation to the lowest excited singlet state (S<sub>1</sub>), these Meldrum-based phenolics undergo fast and efficient non-radiative decay to repopulate the electronic ground state (S<sub>0</sub>). We propose an initial ultrafast twisted intramolecular charge transfer mechanism as these systems evolve out of the Franck-Condon region towards an S<sub>1</sub>/S<sub>0</sub> conical intersection, followed by internal conversion to S<sub>0</sub> and subsequent vibrational cooling. Importantly, we correlate these findings to their long-term photostability upon irradiation with a solar simulator and conclude that these molecules surpass the basic requirements of an industry standard UV filter.</p>
Three-dimensional arrangement of human bone marrow microvessels revealed by immunohistology in undecalcified sections - volume filtering verification
<p>For each of the four ROIs (R1 to R4 in file names) we pick few sub-regions (annotated in R?_legend.png) and show the changes between sections (temporally encoded) from initial (registered) input, marked "1" in video to the final result of volume filtering, marked "5" in video.</p> <p>Subregion number j in ROI number i is bears the video file name "R<i>_verification_volume_-_region_<j>_FullHD.mov".</p>
Datasets to article "Selection history alters attentional filter settings persistently and beyond top-down control"
<p>Single-Subject Behavioral and ERP mean amplitude data for Experiments 1 to 3.</p>
Ecological filtering shapes the impacts of agricultural deforestation on biodiversity
<p>This dataset and associated code are for the manuscript titled "Ecological filtering shapes the impacts of agricultural deforestation on biodiversity", which is due to be published in the journal Nature Ecology & Evolution (accepted on September 20, 2023). The abstract of this manuscript is as follows:</p><p> </p><p>The biodiversity impacts of agricultural deforestation vary widely across regions. Previous efforts to explain this variation have focused exclusively on the landscape features and management regimes of agricultural systems, neglecting the potentially critical role of ecological filtering in shaping deforestation tolerance of extant species assemblages at large geographical scales via selection for functional traits. Here we provide a large-scale test of this role using a global database of species abundance ratios between matched agricultural and native forest sites that comprises 71 avian assemblages reported in 44 primary studies, and a companion database of ten functional traits for all 2,647 species involved. Using meta-analytic, phylogenetic, and multivariate methods, we show that beyond agricultural features, filtering by the extent of natural environmental variability and the severity of historical anthropogenic deforestation shapes the varying deforestation impacts across species assemblages. For assemblages under greater environmental variability – proxied by drier and more seasonal climates under greater disturbance regime – and longer deforestation histories, filtering has attenuated the negative impacts of current deforestation by selecting for functional traits linked to stronger deforestation tolerance. Our study provides a heretofore largely missing piece of knowledge in understanding and managing the biodiversity consequences of deforestation by agricultural deforestation.</p>
Multifunctional blazed gratings for multiband spatial filtering, retroreflection, splitting, and demultiplexing based on C2 symmetric photonic crystals
<p>These datafiles were generated by MATLAB to create a part of the figures in the paper.</p> <p>The work supported partially by the Narodowe Centrum Nauki (projects nos UMO-2015/17/B/ST3/00118 and UMO-2020/39/I/ST3/02413), TUBITAK (Program No. 2221), and projects UBACyT 20020150100028BA, UBACyT 20020190100108BA and CONICET PIP 11220170100633CO.</p> <p> </p>
X-ray diffraction dataset for experimental noise filtering
<p>X-ray diffraction data set for the training of noise filtering algorithms. The data set contains groups of low- and high-counting statistics pairs. The sampling times are mostly 1 (20) seconds for low (high) counting data. Three files in HDF5 format are provided, corresponding to a training, validation and test data set. Each data group contains sequences of 41 consecutive frames, corresponding to a scan along the reciprocal h-direction. Next to the raw data, sampling times and monitor values are included. The test data set additionally contains denoised low-count frames obtained from a pre-trained neural network.</p> <p>Additionally, files containing the trained model weights are included for two different architectures described in the main article (10.1038/s42256-024-00790-1).</p> <p>The data has been recorded on a La<sub>1.88</sub>Sr<sub>0.12</sub>CuO<sub>4</sub> single crystal at the beamline P21.1 at the PETRA III storage ring at DESY in Hamburg, Germany. The scattering intensities were recorded using Dectris Pilatus 100K CdTe detector. The diffractometer was operated with 100 keV photons and the sample was cooled to T ~ 30 K. The data contains different signals such as weak 2D charge density wave order, fundamental Bragg peaks, powder lines, spurions and dead pixels.</p>
Dataset variants used in "Task-Driven Knowledge Graph Filtering Improves Prioritizing Drugs for Repurposing"
<p>This file contains all datasets and variants thereof used in the linked paper. We do not take credit for constructing the datasets, which has been done by the respective original authors (<a href="https://github.com/hetio/hetionet">https://github.com/hetio/hetionet</a>, <a href="https://github.com/gnn4dr/DRKG">https://github.com/gnn4dr/DRKG</a>). For our work we produced modified versions (called "subset" in the file) by applying our metapath based filtering approach. For validation purposed we also constructed ablation versions where one specific type of entities is missing (i.e. "nogene", "noside", etc).</p>
ScienceDex guides
Understand access before you commit
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.