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26 results for “non-stationary”

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dryad40/100

Temporary Allee effects among non-stationary recruitment dynamics in depleted gadid and flatfish populations

We investigated whether low-abundance recruitment dynamics can change in time between compensation and depensation, the latter implying the presence of the Allee effect. For this, we studied the stock-recruitment time series of 17 gadid and flatfish populations in the RAM Legacy Stock Assessment Database using a Bayesian change point model. The recruitment dynamics were represented with the sigmoidal Beverton-Holt and the Saila-Lorda stock-recruitment models, and the parameters of the models were allowed to shift at a priori unknown change points.

opencc-zeroOct 2021View details →

zenodo40/100

Supplement to "Discriminating non-stationary flood hazard effects via probabilistic estimation of sparse residuals from rescued and rated stage–discharge data"

This supplement contains the data and script associated with “Sparse hydrometric data rescue for exploratory analyses of conveyance-driven flood hazard trends and controls,” which has been submitted to a journal for consideration. This supplement is deposited on Zenodo.   Code, Data, and Attribute Descriptions   Uploaded are five directories (indicated in bold font, with their contents detailed below) containing input data and various outputs of the analyses performed for our case study on the Pulangi River at Lumayong (Philippines). Please consider this description equivalent to an omnibus README file for the deposited files. Note that we collected and rescued the hydrometric data herein from the archives of the Water Projects Division (WPD) of the Philippine Department of Public Works and Highways (DPWH).   ●      Pln_R_code contains (1) Pln_RC.R, the R script file, and (2) 240601_Pln_RC.RData, which stores objects generated from the script based on the last execution (on 1 June 2024). The script consists of admittedly too many lines of code (e.g., for data wrangling, formal analyses, and producing figures used in the manuscript) that should have been split into multiple .R files. Apologies. Please be guided by the outline and the comments and kindly reach out lest issues with the code arise.   ●      Pln_GH_PDFs contains the scanned gaugekeeper’s reports of gauge heights (“stages”).    ○      The name of each file varies. For example, Pln-GH-1100.pdf contains daily stage readings for all months in the year 2011. But, if the last two digits are not zeroes, as in Pln-GH-1204.pdf, they refer to the month of that year; in this case, for example, the PDF file contains stage data for the month of April in the year 2012. ○      Each scanned sheet contains sub-daily (with readings at “AM,” “NOON,” and “PM”) and mean daily stages for a given month. ○      Also indicated are the gaugekeeper’s remarks on the daily weather (e.g., “fair,” “cloudy”). Under inclement weather, the gaugekeeper would note the duration of rainfall and its intensity and might, at times, record extra stage readings.   ●      Pln_DM_PDFs contains the following PDF files and a sub-directory: ○      Pln-DM-<XXXXXX>.pdf contains the scanned log for each direct stage—discharge measurement, otherwise known as “gaugings.” Each file is named according to the date of gauging (YYMMDD). For example, the log for the gauging performed on 24 February 2011 can be found in the file Pln-DM-110224.pdf. Data from these gaugings are summarized in Pln-DM-filtered.csv in the Pln_In_CSVs directory. ■      The readability of each file varies based on the original quality of the original paper-format data. ■      The first page in each file contains, on the left side, a summary of the gauging data and metadata (e.g., date of measurement, number of gauging verticals or “sections” used, method of crossing or measuring the cross-section), and on the right side, the velocity—area readings at each gauging vertical. ■      The second page in each file contains the plotted cross-section of the channel at the time of measurement. ○      Pln-RC.pdf contains various other paper-format data and some annotations relevant to the historical rating at the station. ■      P. 1: The hydrographic engineer’s comment (dated 19 January 2012) on the evaluation of the discharge data, specifically detailing the periods of validity of the rating curves developed for different sub-periods of monitoring. ■      PP. 2—3: A summary table of all the gaugings performed from 1983 to 2010 whose logs were no longer retrievable (and hence not included as a DM-PDF file in this directory). ■      PP. 4—5: Plots of the official stage—discharge rating curves developed by DPWH hydrographers. ■      PP. 6—8: Rating tables used to convert daily mean stages to deterministic discharge estimates. Two of these rating tables were digitized and can be found in the Pln_RatingTables sub-directory in Pln_In_CSVs. ■      PP. 9—22: Daily stage (m) and its corresponding daily discharge (L/s) for the 2004—2010 sub-period. The stages were digitized and included in Pln-H_arch.csv in the Pln_In_CSVs directory. ○      Pln_DM_unused contains the PDF files of logs (including data and metadata) corresponding to the gaugings that were excluded from our analysis following our filtering step for gauging location consistency.   ●      Pln_In_CSVs contains the following CSV files and two sub-directories; these files were used as inputs to the R script for formal analyses: ○      Pln-H_arch.csv contains the mean daily stage values [“H_bar_arch”] (m) for every day in the 2004—2020 sub-period [“Date”] (YYYY-MM-DD). The stages in this file are already corrected for gross errors. ○      Pln-DM-filtered.csv contains the following information on the gaugings performed on the Pulangi at Lumayong (1983—2020): (i) date [“Date”] (YYYY-MM-DD); (ii) stage [“H”] (m); (iii) discharge in L/s [“Q_lps”] and m3/s [“Q_cms”]; (iv) wetted area [“A_sqm”] (m2); (v) mean flow velocity [“Vel_mps”] (m/s); (vi) channel width [“W_m”] (m); (vii) mean flow depth [“D_ave_m”] (m); (viii) location of the measurement cross-section with respect to the staff gauge, with negative values meaning downstream of the gauge and positive values meaning upstream of the gauge [“XS_loc_wrt_gage”]; (ix) maximum flow depth [“Max_Depth_m”] (m); and (x) minimum streambed elevation [“MINSBE”] (m). Note that this file includes only gaugings that passed our filtering step for measurement location consistency. ○      Pln-DM_oview.csv contains information on the temporal coverage (bounded by “Start_date” and “End_date”) of the available hydrometric data from the station archives. ○      Pln-H_sample_GrossE_corr.csv contains a sample sub-period (2017-06-15 through 2017-11-30) and the corresponding values of stages (m), uncorrected [“H_uncorrected”] and corrected for gross errors [“H_corrected”]. This CSV file was used as an input to the R script to produce one of the figures in the manuscript.  ○      Pln-XS-csv.csv contains data on the gauging transects: gauging ID [“GaugingID”]; date [“Date”] (YYYY-MM-DD); lateral distance from a fixed initial point [“Lat_distance”] (m); width of the gauging vertical [“Width_vert..m.”] (m); depth relative to the water surface [“Depth..m.”] (m); stage at the gauging vertical [“H_m_vert..m.”] (m); and elevation with respect to a fixed arbitrary datum at the station [“Elev..m.”] (m). ○      Pln_Rating_Tables contains two rating tables, Pln-DM - RatingTable_A.csv and Pln-DM - RatingTable_B.csv, prepared and used by DPWH hydrographers for converting stage values to deterministic discharge estimates for the Pulangi River at Lumayong for the 1980s—early 2000s sub-period. Each rating table contains columns for stage [“H”], discharge in L/s [“Q_lps”], and discharge in m3/s [“Q_cms”]. ○      Pln_Q_rated contains two CSV files: Pulangi.csv has the columns “YEAR”, “DAY”, and every month of the year [“JAN” through “DEC”] for the 1983—2003 sub-period, with the values under each month column indicating the deterministic discharge estimates in L/s; Pulangi_trunc.csv contains similarly formatted data, but for the 2009—2010 sub-period.   ●      Pln_Out_CSVs contains two CSV files, the primary outputs of the hydrometric data rescue effort. ○      Pln_Q_recon.csv contains the reconstructed discharge time series (1983—2020) and its associated uncertainties at the 95% credibility interval. It has the following columns: date [“Date”] (YYYY-MM-DD); daily stage [“H”] (m); lower bound of the discharge estimate [“Q_lwr”] (m3/s); median discharge estimate [“Q_med”] (m3/s); and the upper bound of the discharge estimate [“Q_upr”] (m3/s). Pln_H_recon.csv contains the reconstructed and quality-controlled stage time series (1983—2020). It has the following columns: date [“Date”] (YYYY-MM-DD); mean daily stage that has been corrected for gross errors, but not yet filtered through other quality checks [“H_bar_arch”] (m); quality check for low outliers [“Low_Outlier”] (TRUE/FALSE); quality check for flatliners [“Flatliner”] (TRUE/FALSE); difference between the stage values on day i and day i-1 [“Daily_Step”] (m); quality check for large steps [“Large_Step”] (TRUE/FALSE); and the corrected and quality-controlled mean daily stage values [“H”] (m).

opencc-by-4.0Jun 2024View details →

zenodo40/100

Non-stationary SWM dataset

Dataset to support WRR manuscript 'A hybrid, non-stationary Stochastic Watershed Model (SWM) for uncertain hydrologic projections under climate change' Supports code at public GitHub repository: <a href="https://github.com/zpb4/Nonstationary-SWM">https://github.com/zpb4/Nonstationary-SWM</a>

opencc-by-4.0Feb 2023View details →

dryad40/100

Temporary Allee effects among non-stationary recruitment dynamics in depleted gadid and flatfish populations

Open the record for dataset details and reuse information.

publicOct 2021View details →

dryad36/100

Theoretical analysis of superadiabatic combustion for non-stationary filtration combustion by excess enthalpy function

The superadiabatic combustion for non-stationary filtration combustion is analytically studied. The non-dimensional excess enthalpy function (H) equation is theoretically derived based on a one-dimensional, two-temperature model. In contract to the H equation for the stationary filtration combustion, a new term, which takes into account the effect of non-dimensional combustion wave speed, is included in H equation for transient filtration combustion. The governing equations with boundary conditions are solved by commercial software Fluent. The predictions show that the maximum non-dimensional gas and solid temperatures in the flame zone are greater than 3 for equivalence ratio of 0.15. An examination of the four source terms in the H equation indicates that the thermal conductivity ratio (Γs) between the solid and gas phases is the dominative one among the four terms and basically determines H distribution. For lean premixed combustion in porous media, the superadiabatic combustion effect is more pronounced for the lower Γs.

opencc-zeroAug 2020View details →

dryad36/100

Data from: Non-stationary climate-salmon relationships in the Gulf of Alaska

Studies of climate effects on ecology often account for non-stationarity in individual physical and biological variables, but rarely allow for non-stationary relationships among variables. Here, we show that non-stationary relationships among physical and biological variables are central to understanding climate effects on salmon (Onchorynchus spp.) in the Gulf of Alaska during 1965-2012. The relative importance of two leading patterns in North Pacific climate, the Pacific Decadal Oscillation (PDO) and North Pacific Gyre Oscillation (NPGO), changed around 1988/89 as reflected by changing correlations with leading axes of sea surface temperature variability. Simultaneously, relationships between the PDO and Gulf of Alaska environmental variables weakened, and long-standing temperature-salmon and PDO-salmon covariance declined to zero. We propose a mechanistic explanation for changing climate-salmon relationships in terms of non-stationary atmosphere-ocean interactions coinciding with changing PDO-NPGO relative importance. We also show that regression models assuming stationary climate-salmon relationships are inappropriate over the multidecadal time scale we consider. Relaxing assumptions of stationary relationships markedly improved modeling of climate effects on salmon catches and productivity. Attempts to understand the implications of changing climate patterns in other ecosystems might also be aided by the application of models that allow associations among environmental and biological variables to change over time.

opencc-zeroDec 2017View details →

zenodo36/100

Data from: "A framework for performing comparative LCA between repairing flooded houses and construction of dikes in non-stationary climate with changing risk of flooding"

In the paper "A framework for performing comparative LCA between repairing flooded houses and construction of dikes in a non-stationary climate with changing risk of flooding", life cycle assessment is used to compare two ways to maintain the state of a coastal urban area in a changing climate with increasing flood risk. On one side, the construction of a dike, a hard and proactive scenario, is modeled using a bottom-up approach. On the other, the systematic repair of houses flooded by sea surges, a post-disaster measure, is assessed using a Monte Carlo simulation allowing for aleatory uncertainties in predicting future sea level rise and occurrences of extreme events. Two metrics are identified, normalized mean impacts and probability of dike being most efficient. The methodology is applied to three case studies in Denmark representing three contrasting areas, Copenhagen, Frederiksværk, and Esbjerg. For all case studies the distribution of the calculated impact of repairing houses is highly right skewed, which in some cases has implications for the comparative LCA. This dataset contains the underlying data to support the findings of the paper. In particular, two sets of characterized environmental impacts are reported: (1) the impacts of flood-related repairs summed over a century, for each Monte Carlo simulation and (2) the impacts of building a dam. Both sets of results are reported for each of the three cities studied.

opencc-by-4.0Nov 2023View details →

zenodo36/100

Whistler waves and two-stream instabilities at non-stationary quasi-perpendicular collisionless shocks

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opencc-by-4.0Dec 2023View details →

dryad36/100

Theoretical analysis of superadiabatic combustion for non-stationary filtration combustion by excess enthalpy function

Open the record for dataset details and reuse information.

publicSep 2020View details →

dryad36/100

Data from: Non-stationary climate-salmon relationships in the Gulf of Alaska

Open the record for dataset details and reuse information.

publicOct 2018View details →

dryad36/100

Phylogenetic accuracy under non-stationary and non-homogeneous conditions: A simulation study

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publicDec 2025View details →

zenodo32/100

Data from the article "The mitochondrial phylogeny of land plants shows support for Setaphyta under non-stationary substitution models"

Data from the article: "The mitochondrial phylogeny of land plants shows support for Setaphyta under non-stationary substitution models" Filipe de Sousa, Peter Civáň, João Brazão, Peter G. Foster, Cymon J. Cox   These data are divided in four folders: * 1_36_gene_nt_alignments_&_trees - contains 36 single gene nucleotide alignments and the corresponding trees inferred from a MCMC analysis on the program p4 * 2_36_gene_aa_alignments_&_trees - contains 36 single gene amino acid alignments and the corresponding trees inferred from a MCMC analysis on the program p4 * 3_concatenated_alignments_&_trees - contains the nucleotide, codon-degenerate and amino acid alignments of 36 concatenated genes and the corresponding trees inferred from MCMC analyses on the programs p4 and phylobayes with composition homogeneous, tree-heterogeneous and site-heterogeneous models; trees correspond to figures S1-S7 on the online supplemental file. * 4_concatenated_ML_trees - contains the ML trees from the analyses of the concatenated datasets (nucleotide, codon degenerate and amino acid).

opencc-by-4.0Nov 2019View details →

dryad32/100

Data from: Multi-alternative decision making with non-stationary inputs

One of the most widely implemented models for multi-alternative decision-making is the multihypothesis sequential probability ratio test (MSPRT). It is asymptotically optimal, straightforward to implement, and has found application in modelling biological decision-making. However, the MSPRT is limited in application to discrete ('trial-based'), non-time-varying scenarios. By contrast, real world situations will be continuous and entail stimulus non-stationarity. In these circumstances, decision-making mechanisms (like the MSPRT) which work by accumulating evidence, must be able to discard outdated evidence which becomes progressively irrelevant. To address this issue, we introduce a new decision mechanism by augmenting the MSPRT with a rectangular integration window and a transparent decision boundary. This allows selection and de-selection of options as their evidence changes dynamically. Performance was enhanced by adapting the window size to problem difficulty. Further, we present an alternative windowing method which exponentially decays evidence and does not significantly degrade performance, while greatly reducing the memory resources necessary. The methods presented have proven successful at allowing for the MSPRT algorithm to function in a non-stationary environment.

opencc-zeroDec 2015View details →

zenodo32/100

Data for Standard Codon Substitution Models Overestimate Purifying Selection for Non-Stationary Data

Codon-aligned, filtered alignments for Kaehler et al. (2016) (https://peerj.com/preprints/2218/). Please refer to preprint for preparation details. Data obtained from Ensembl (http://www.ensembl.org/) and antbase (http://antbase.org).

opencc-by-nc-4.0Dec 2016View details →

zenodo32/100

Dataset: A Non-Stationary Bias Adjustment Method for improving the Inter-annual Variability and Persistence of Projected Precipitation

This dataset includes: (1) unbiased data using a novel non-stationary bias adjustment methodology specifically tailored for environmental variables exhibiting sporadic events characterized by substantial intensity variability; (2) the parameters of the non-stationary probability distributions using marinetools.temporal. The methodology involves establishing a probability threshold to adapt the occurrence of precipitation events and employing a non-stationary theoretical and parametric quantile mapping to adjust associated biases. The dataset is part of the results obtained after the application of the methodology to daily precipitation projections from seven regional climatic models of the RCP 8.5 scenario spanning 2006-2100, alongside historical concurrent data from projections and observations spanning 1970-2005. Its efficacy is compared a widely used quantile mapping method, revealing notable differences in the performance of the methods concerning the distribution of events throughout the year and the behaviour of mean and extreme intensity values. The proposed method demonstrates promising potential in reducing uncertainty associated with systematic errors in inter-annual precipitation variability. This bears significance in evaluating hydrological responses and its associated impacts particularly in semi-arid mountainous basins.

opencc-by-4.0Sep 2024View details →

dryad32/100

Data from: Multi-alternative decision making with non-stationary inputs

Open the record for dataset details and reuse information.

publicAug 2016View details →

dryad32/100

Data from: Genetic distance for a general non-stationary Markov substitution process

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publicJan 2015View details →

dryad28/100

Data from: Novel Fourier quadrature transforms and analytic signal representations for nonlinear and non-stationary time series analysis

The Hilbert transform (HT) and associated Gabor analytic signal (GAS) representation are well-known and widely used mathematical formulations for modeling and analysis of signals in various applications. In this study, like the HT, to obtain quadrature component of a signal, we propose novel discrete Fourier cosine quadrature transforms (FCQTs) and discrete Fourier sine quadrature transforms (FSQTs), designated as Fourier quadrature transforms (FQTs). Using these FQTs, we propose sixteen Fourier quadrature analytic signal (FQAS) representations with following properties: (1) real part of eight FQAS representations is the original signal and imaginary part of each representation is FCQT of real part, (2) imaginary part of eight FQAS representations is the original signal and real part of each representation is FSQT of imaginary part, (3) like the GAS, Fourier spectrum of the all FQAS representations has only positive frequencies, however unlike the GAS, real and imaginary parts of FQAS representations are not orthogonal. The Fourier decomposition method (FDM) is an adaptive data analysis approach to decompose a signal into a set Fourier intrinsic band functions. This study also proposes new formulations of the FDM using discrete cosine transform with GAS and FQAS representations, and demonstrate its efficacy for improved time-frequency-energy representation and analysis of many real-life nonlinear and non-stationary signals.

opencc-zeroDec 2017View details →

zenodo28/100

The observational stationary dataset and the Python scripts for the non-stationary data concocting.

dataset and script

opencc-by-4.0Oct 2022View details →

dryad28/100

Data from: A new method of Bayesian causal inference in non-stationary environments

Bayesian inference is the process of narrowing down the hypotheses (causes) to the one that best explains the observational data (effects). To accurately estimate a cause, a considerable amount of data is required to be observed for as long as possible. However, the object of inference is not always constant. In this case, a method such as exponential moving average (EMA) with a discounting rate is used to improve the ability to respond to a sudden change; it is also necessary to increase the discounting rate. That is, a trade-off is established in which the followability is improved by increasing the discounting rate, but the accuracy is reduced. Here, we propose an extended Bayesian inference (EBI), wherein human-like causal inference is incorporated. We show that both the learning and forgetting effects are introduced into Bayesian inference by incorporating the causal inference. We evaluate the estimation performance of the EBI through the learning task of a dynamically changing Gaussian mixture model. In the evaluation, the EBI performance is compared with those of the EMA and a sequential discounting expectation-maximization algorithm. The EBI was shown to modify the trade-off observed in the EMA.

opencc-zeroMay 2020View details →

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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.

allen-brain-atlas

neuroscienceopenDocumentation, web resources, and API references are available online.

Last verified 2026-04-30Open record

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.

abode-home-cage

behavioral-neuroscienceopenThe DataShare record exposes download links for annotations, documentation, license text, and the zipped per-snippet data directory.

Last verified 2026-04-30Open record

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.

dandi-nwb

electrophysiologyopenPublished Dandiset metadata and archive endpoints are available through the production DANDI API.

Last verified 2026-04-30Open record

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.

ibl

behavioral-neuroscienceopenPublic sessions can be searched and loaded from the IBL public data server through ONE.

Last verified 2026-04-29Open record

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.

openneuro

neuroscienceopenPublished datasets are available on demand over the internet.

Last verified 2026-04-29Open record