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914 results for “filter”
Audio Examples for "Directional Frequency Filtering of Recordings in Spherical Harmonics Domain for Innovative Noise Reduction Strategies"
<p>This is a collection of audio examples of the processing corresponding to the master thesis "Directional Frequency Filtering of Recordings in Spherical Harmonics Domain for Innovative Noise Reduction Strategies"<br> The examples (ambisonics and binaural) contain recordings of moving sources in an anechoic chamber, which were made within different scenes partly containing noise barriers. Furthermore the simulation of noise barriers was implemented using directional filtering within a plane wave decomposition of the signals in sh domain.</p>
Data from: Environmental filtering of macroinvertebrate traits influences ecosystem functioning in a large river floodplain
<p>The Biodiversity-Ecosystem Function hypothesis postulates that higher biodiversity is correlated with faster ecosystem process rates and increased ecosystem stability in fluctuating environments. Exhibiting high spatio-temporal habitat diversity, floodplains are highly productive ecosystems, supporting communities that are naturally resilient and highly diverse. </p> <p>We examined linkages among floodplain wetland habitats, invertebrate communities and their associated traits, and ecosystem function across 60 sites within the floodplain wetlands of the lower Wolastoq | Saint John River, New Brunswick, using structural equation modelling and Threshold Indicator Taxa ANalysis (TITAN2). </p> <p>We identified key environmental filters structuring invertebrate communities, by linking increased niche differentiation through shoreline change, flood pulse dynamics, and macrophyte bed complexity with increased taxa and functional diversity. </p> <p>Examination of traits linked to ecosystem functions revealed that more resilient wetlands with balance between primary productivity and decomposition as carbon sources were associated with greater functional evenness and richness, while habitat patches with elevated decomposition rates had lower functional richness, reflecting a simplified, more disturbed habitat. </p> <p>While our more complex overarching SEM model was ultimately compromised by an overspecified number of pathways, our results nevertheless are indicative of a divergence between wetland and riverine ecosystems in their relationships linking biodiversity and ecosystem function, illustrating how to define ecosystem health in wetland habitats, and demonstrating how critical functions support healthy wetland habitats by providing increased resilience to disturbance.</p>
Do large-scale associations in birds imply biotic interactions or environmental filtering?
<p><strong>Aim</strong>: There has been a wide interest in the effect of biotic interactions on species' occurrences and abundances at large spatial scales, coupled with a vast development of the statistical methods to study them. Still, the evidence whether the effects of within-trophic level biotic interactions (e.g. competition and heterospecific attraction) are discernible beyond local scales remains inconsistent. Here, we present a novel hypothesis-testing framework based on joint dynamic species distribution models (JDSDMs) and functional trait similarity to dissect between environmental filtering and biotic interactions. </p> <p><strong>Location</strong>: France and Finland. </p> <p><strong>Taxon</strong>: Birds. </p> <p><strong>Methods</strong>: We estimated species-to-species associations within a trophic level, independent of the main environmental variables (mean temperature and total precipitation) for common species at large spatial scale with joint dynamic species distribution models (VAST). We created hypotheses based on species' functionality (morphological and/or diet dissimilarity) and habitat preferences about the sign and strength of the pairwise spatio-temporal associations to estimate the extent to which they result from biotic interactions (competition, heterospecific attraction) and/or environmental filtering. </p> <p><strong>Results</strong>: Spatio-temporal associations were mostly positive (80%), followed by random (15%), and only 5% were negative. Negative spatio-temporal associations in different communities were due to a few species when they existed. The relationship between spatio-temporal association and functional dissimilarity among species was negative, which fulfills the predictions of both environmental filtering and heterospecific attraction. </p> <p><strong>Main conclusions: </strong>We showed that processes leading to species aggregation (mixture between environmental filtering and heterospecific attraction) seem to dominate assembly rules, and we did not find evidence for competition. Altogether, hypothesis-testing framework based on joint dynamic species distribution models and functional trait similarity is beneficial in ecological interpretation of species-to-species associations from the long-term large-scale data. </p>
Filter and sedimentation place
<p>Filter and sedimentation place.</p> <p>Photo taken on 14.02.2016 in Bulu, Nafra circle, West Kameng, Arunachal Pradesh, India.</p>
Database of 16S sequences from SILVA (r114), filtered, curated and annotated to be used easily by programs of taxonomic assignments
<p>The database used for the taxonomic assignment of reads generally comes from the SILVA database (http://www.arb-silva.de/). The logic behind this database is to use the information from the best one to the worst one. This is why the curated database was splitted in two parts : the [C] sequences for Complete sequences in terms of taxonomy, and the [I] and [E] sequences, for Incomplete and Environmental sequences.</p> <p>Each sequence included into the database must have a specific format summarizing all needed information (example below):<br> >[I]AACY020336309;Archaea(superkingdom);Euryarchaeota(phylum);Thermoplasmata(class);Thermoplasmatales(order);Marine_Group_II(no_rank);;marine_metagenome</p> <p>This sequence is an incomplete one ([I]), with a specific accession number from NCBI or SILVA, or another database (AACY020336309). Then, all taxonomic data is separated using ';' characters, for each considered level (superkingdom, phylum, <br> class, order, family, and genus). The species name is the last one and separated by two ';' characters from the rest of the descriptive line. Finally, the descriptive line must not contain specific characters like spaces. If one or several levels are unknown, this is indicated by 'no_rank'.</p> <p>Another example here for [C] sequences:<br> >[C]AAAK03000010;Bacteria(superkingdom);Firmicutes(phylum);Bacilli(class);Lactobacillales(order);Enterococcaceae(family);Enterococcus(genus);;Enterococcus_faecium_DO<br> This sequence is a complete one ([C]), with a specific accession number from NCBI or SILVA, or another database (AACY020187844). Then, all taxonomic data is separated using ';' characters, for each considered level (superkingdom, phylum, <br> class, order, family, and genus). The species is the last one and separated by two ';' characters from the rest of the descriptive line. Complete sequences must have six levels of information (superkingdom, phylum, class, order, family, and genus). If it is not the case, the sequence will be considered as Incomplete ([I]) (between three and five levels), or Environmental ([E]) (with only the superkingdom and the phylum levels).</p> <p>Another example here for [E] sequences:<br> >[E]U59968;Archaea(superkingdom);Thaumarchaeota(phylum);Soil_Crenarchaeotic_Group(SCG)(no_rank);;uncultured_crenarchaeote<br> This sequence is a environmental one ([E]), with a specific accession number from NCBI or SILVA, or another database (U59968). Then, all taxonomic data is separated using ';' characters, for each considered level (superkingdom, phylum, class, order, family, and genus). The species is the last one and separated by two ';' characters from the rest of the descriptive line. Complete sequences <br> must have six levels of information (superkingdom, phylum, class, order, family, and genus). If it is not the case, the sequence will be considered as Incomplete ([I]) (between three and five levels), or Environmental ([E]) (with only the superkingdom and the phylum levels).</p> <p>More details on the steps defined to clean and define this new database can be available on demand (sebastien.terrat@inra.fr).</p>
Scanning electron microscopy (SEM) images of particulate matter collected on air filters
<p>Airborne PM sampling was conducted within a larger study on the PM composition of different areas in Santa Rosa, La Pampa, Argentina by Prof. Dr. Mendez Mariano. Airborne PM10 samples were collected on commercial 47mm diameter PTFE membrane filters (Image 1-blank) and Nylon filters (Image 2-blank). The PM10 was collected using an electrostatic precipitator coupled with the Easy Dust Generator (EDG). Filters were analysed using a Scanning Electron Microscope (Phenom™ ProX Desktop, Thermofisher). Images were taken using an accelerating voltage of 15 kV. SEM-EDX results are presented in this dataset.</p>
CANOPUS dataset filtered with NeurIPS MS/MS structures
<p>The 4,175,091 CANOPUS structures (<span>https://doi.org/10.1038/s41587-020-0740-8</span>) were filtered by a hit (MCES-distance <= 2) to a structure of the NeurIPS MS/MS dataset (https://zenodo.org/doi/10.5281/zenodo.11210205). 2304 structures from the CANOPUS dataset did not have SMILES and were excluded. The MS/MS-dataset structures were PubChem-standardized with 3 compounds failing standardization.</p>
ec-filter dataset
<p>This contains two datasets used for demonstrate the dangers and solutions for post search filter in crosslinking mass-spectrometry. A dataset of search results for mycoplasma pneumonia acquisitions and escherichia coli. Both where searched against a combined database of all e.coli and mycoplasma pneumonia proteins.</p> <p>These are results without any cut-off and are the base of testing if a filter or processing step is actually affecting decoys differently then target false positives. The idea being that these search results provide an decoy independent set of known false positive matches; all matches involving e.coli peptides to mycoplasma spectra and all matches involving mycoplasma pneumonia peptides to e.coli spectra. In the original use case the data where used to detect if a filter, that uses match external information to filter individual matches, results in an underrepresentation of decoys when compared to these secondary known false positives and how at least no contradiction was found when applying teh ec-filter style of applying the information.</p> <p> </p> <p>The second dataset is a set of FDR results for 2% unique residue pair FDR of an yeast 26S Proteasome acquisition run with and without using the ec-filter and each of tzhese with and without xiFDR in built boosting. The spectra where searched against increasingly larger databases to show the effect of filtering the results depending on the database size – both in terms of present and assumed non-present proteins.</p> <p> </p>
Trained Random Forest Model for PNW Seismic Event Classification Trained on 150s waveforms (P-50, P+100), 50 Hz, and 1-10 Hz BP Filtered
<p>This dataset contains three trained random forest models named as following - </p> <ul> <li>P_10_100_F_1_10_50.joblib - This is a model trained on 110s long waveforms (origin time - 10, origin time +100) in case of earthquakes and explosions and (first arrival pick -10, first arrival pick + 100) in case of surface events, the waveforms are tapered using 10% cosine taper, bandpass filtered between 1-10 Hz using Butterworth four corner filter, normalized and resampled to 50 Hz. </li> <li>P_50_100_F_1_10_50.joblib </li> <li>P_10_30_F_1_15_50.joblib. </li> </ul> <p>And also the standard scaler parameters for each features that will be used to normalize them. </p>
Chromophore-driven optical path reduction as an indirect inner filter effect correction strategy in fluorescence microplate assays - experimental data
<p>Experimental data for the paper entitled <em>Chromophore-driven optical path reduction as an indirect inner filter effect mitigation strategy in fluorescence microplate assays</em> (<a title="Persistent link using digital object identifier" href="https://doi.org/10.1016/j.saa.2025.127049" target="_blank" rel="noreferrer noopener"><span><span>https://doi.org/10.1016/j.saa.2025.127049</span></span></a>). </p> <p>An Excel file with multiple worksheets is provided for the following:</p> <p>1. Fluorescence data:</p> <p>The worksheets contain fluorescence values measured in tetraplicates using two microplate readers (Tecan Spark M10, Tecan, Austria and SpectraMax iD3, Molecular Devices, USA), with baseline values recorded in octuplicates. The results were averaged and baseline-corrected. Detailed notes on the titration experiments are included in the manuscript. Data include both IFE-uncorrected fluorescence and fluorescence corrected (fully or partially) by the addition of an absorbing chromophore.</p> <p>2. Absorbance data:</p> <p>All measured absorbance values obtained using the Tecan Spark M10 microplate reader with UV-Vis transparent microplates are included. The absorbance values at specific wavelengths suitable for the Lakowicz IFE correction method or for determining the concentration of the compound are given separately.</p> <p>3. Fluorescein spectra:</p> <p>UV-Vis and fluorescence excitation/emission spectra for highly dilute fluorescein concentrations where the inner filter effect (IFE) is negligible are reported. These measurements were performed to obtain “true” excitation and emission spectra without the influence of IFE quenching effects.</p> <p>4. ZINFE/NINFE IFE corrections:</p> <p>The dataset contains the results of ZINFE/NINFE IFE corrections (<a href="https://doi.org/10.1021/acs.analchem.2c01031">https://doi.org/10.1021/acs.analchem.2c01031</a>) applied to the fluorescence data and processed using the web service available at <a href="https://ninfe.science">https://ninfe.science</a>.</p> <p>The notation of the fluorophores and microplates is the same as in the manuscript. For reasons of visual clarity, the numerical titration indices are not in subscript.</p> <p> </p>
Plasticity of the selectivity filter is essential for permeation in lysosomal TPC2 channels
<p>Molecular dynamics raw data (input files and skipped example trajectories) for the associated manuscript "Plasticity of the selectivity filter is essential for permeation in lysosomal TPC2 channels" in PNAS.</p>
PatchMAN BSA filtering databases and benchmark input and natives
<p>This repository contains the list of unbound receptors, peptides and natives that was used for PatchMAN BSA filtering paper.</p> <p> </p> <p>It also containts the databases that are used 1) search with MASTER, 2) extraction of fragments with MASTER.</p>
Figure 5. Algorithm A5pseudocode-Efficient Filtering of Noisy Fingerprint Images
<p>A5&apply thresholds globally across the image (Figure 5.);</p>
TCGA filtered dataset used in driverMAPS paper
<p>Filtered mutation lists files for 20 cancer types from TCGA. This is the dataset used for running MAPS and other competitor software in the paper. This dataset is processed based on raw files from TCGA GDAC website (https://confluence.broadinstitute.org/display/GDAC/Home). Please follow TCGA data use policy when using this dataset.</p>
Mutation Calls from the TCGA MC3 project (filtered)
<p>The Cancer Genome Atlas (TCGA) cancer genomics dataset includes over 10,000 tumor-normal exome pairs across 33 different cancer types, in total >400 TB of raw data files requiring analysis. Here we describe the Multi-Center Mutation Calling in Multiple Cancers project, our effort to generate a comprehensive encyclopedia of somatic mutation calls for the TCGA data to enable robust cross-tumor-type analyses. Our approach accounts for variance and batch effects introduced by the rapid advancement of DNA extraction, hybridization-capture, sequencing, and analysis methods over time. We present best practices for applying an ensemble of seven mutation-calling algorithms with scoring and artifact filtering. The dataset created by this analysis includes 3.5 million somatic variants and forms the basis for PanCan Atlas papers. The results have been made available to the research community along with the methods used to generate them.</p> <p>This dataset was filtered for the 2018 PanCancer analysis, according to the methods specified in Bailey, Tokheim, Porta-Pardo et al, 2018 ( http://dx.doi.org/10.1016/j.cell.2018.02.060 )</p> <p> </p>
Cerucuk Filter Modified (CFM)
<p>Cerucuk Filter Modified (CFM) function as a filter to decrease TSS concentration and control sedimentation control due to runoff in drainage channels. Installation before and after sediment traps.</p>
Supplementary Data for Massively Parallel Implicit Equal-Weights Particle Filter for Ocean Drift Trajectory Forecasting
<p>This data repository is provided as a supplement to the paper *Massively Parallel Implicit Equal-Weights Particle Filter for Ocean Drift Trajectory Forecasting* written by Håvard Heitlo Holm, Martin Lilleeng Sætra and Peter Jan van Leeuwen. It contains the complete datasets (initial conditions and results of the ensemble simulations) obtained from the experiments presented therein.</p> <p>This data set is generated by, and can be further post-processed and visualized by, the code published as *metno/gpu-ocean: Supplementary Software for Massively Parallel Implicit Equal-Weights Particle Filter for Ocean Drift Trajectory Forecasting* by Håvard Heitlo Holm, Martin Lilleeng Sætra and André Rigland Brodtkorb (DOI 10.5281/zenodo.3458291). </p> <p> </p>
Towards Symmetry Driven and Nature Inspired UVA Filter Design
<p>In plants, sinapate esters offer crucial protection from the deleterious effects of ultraviolet radiation exposure. These esters are a promising foundation for designing UV filters, particularly for the UVA region (400 – 315 nm), where adequate photoprotection is currently lacking. Whilst sinapate esters are highly photostable due to a cis-trans (and vice versa) photoisomerization, the cis-isomer can display increased genotoxicity; an alarming concern for current cinnamate ester-based human sunscreens. To eliminate this potentiality, here we synthesize a sinapate ester with equivalent cis- and trans-isomers. We investigate its photostability through innovative ultrafast spectroscopy on a skin mimic, thus modelling the as close to true environment of sunscreen formulas. These studies are complemented by assessing endocrine disruption activity and antioxidant potential. We contest, from our results, that symmetrically functionalized sinapate esters may show exceptional promise as nature-inspired UV filters in next generation sunscreen formulations.</p>
GPS timeseries raw and filtered
<p>The data files include the raw and ICA filtered GPS timeseries for the five-minute (early postseismic of the five six days), and daily timeseries (the first two years).</p>
ULTRAMICROBACTERIA AND FILTERABLE BACTERIA IN THE PLANKTON OF LAKE BAIKAL
<p>In Lake Baikal, the number, diversity and structure of femtoplankton – bacteria passing through filters with a pore size of 0.2 μm were studied for the first time using a complex of methods. The bacterial abundance in the femtoplankton fraction was 7×10<sup>4</sup> cells/ml in the 0-50 m water layer as measured by epifluorescence microscopy, and their contribution to the total bacterial number reached an average of 4.4%. High throughput sequencing of 16S rRNA gene fragments revealed a significant genetic and taxonomic diversity of femtobacterioplankton in the pelagic and littoral zones of the lake. Dominant and minor phyla, orders, families, genera, and phylotypes of bacteria were identified in two fractions of the Lake Baikal bacterioplankton larger and smaller than 0.2 µm; the contribution of ultrasmall bacteria to the taxonomic composition of microbial communities in different parts of the lake was determined. Significant differences in the microbiomes of bacterioplankton and femtobacterioplankton fractions were revealed, and the peculiarities of ultramicrobacteria composition were described. The results showed an important role of ultrasmall bacteria in the Lake Baikal ecosystem. </p> <p><strong>This repository contains raw sequencing data from DNA metabarcoding and metadata with samples description for the current study.</strong></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.