Find research datasets worth reusing

Value-based Software Engineering: A Systematic Mapping Study

Abstract Background: Integrating value-oriented perspectives into the principles and practices of software engineering is fundamental to ensure that software development activities address key stakeholders’ views and also balance short-and long-term goals. This is put forward in the discipline of value-based software engineering (VBSE) Aim: This study aims to provide an overview of VBSE with respect to the research efforts that have been put into VBSE. Method: We conducted a systematic mapping study to classify evidence on value definitions, studies’ quality, VBSE principles and practices, research topics, methods, types, contribution facets, and publication venues. Results: From 143 studies we found that the term “value” has not been clearly defined in many studies. VB Requirements Engineering and VB Planning and Control were the two principles mostly investigated, whereas VB Risk Management and VB People Management were the least researched. Most studies showed very good reporting and relevance quality, acceptable credibility, but poor in rigor. The main research topic was Software Requirements and case study research was the method used the most. The majority of studies contribute toward methods and processes, while very few studies have proposed metrics and tools. Conclusion: We highlighted the research gaps and implications for research and practice to support VBSE.

opencc-zeroMay 2023View details →

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Data for: Genetic control of grain amino acid composition in a UK soft wheat mapping population

Wheat is a major source of nutrients for populations across the globe, but the amino acid composition of wheat grain does not provide optimal nutrition. The nutritional value of wheat grain is limited by low concentrations of lysine (the most limiting essential amino acid) and high concentrations of free asparagine (precursor to the processing contaminant acrylamide). There are currently few available solutions for asparagine reduction and lysine biofortification through breeding. In this study, we investigated the genetic architecture controlling grain-free amino acid composition and its relationship to other traits in a Robigus × Claire doubled haploid population. Multivariate analysis of amino acids and other traits showed that the two groups are largely independent of one another, with the largest effect on amino acids being from the environment. Linkage analysis of the population allowed the identification of QTL controlling free amino acids and other traits, and this was compared against genomic prediction methods. Following the identification of a QTL controlling free lysine content, wheat pangenome resources facilitated analysis of candidate genes in this region of the genome. These findings can be used to select appropriate strategies for lysine biofortification and free asparagine reduction in wheat breeding programmes.

opencc-by-4.0Apr 2023View details →

Interactive web map of local heritage sites in Inhambane province, Mozambique

Interactive web map containing locally protected forest patches, ceremonial places, archaeological sites and other landscape features making up cultural heritage of Inhambane province, Mozambique. Using geonarratives and local cartography, information about the location of locally protected forest patches, ceremonial places and other landscape features (e.g., lakes, caves and wells) making up cultural heritage was provided by local leaders and communities stewarding local heritage sites in Inhambane province. Data about archaeological sites is derived from the study done by Adamowicz and Nhatule (2011). Data about protected areas was derived from National Cartography and Remote Sensing Centre in Mozambique. The interactive web map was produced using the qgis2web plugin built-in the QGIS.  Adamowicz, L., & Nhatule, E. (2011). Environment and social impact assessment for the proposed exploration in EPC area “A”. Maputo: Archaeological Circle of Cultural Heritage.

opencc-by-4.0Jul 2022View details →

Annual Average Suspended Sediment Concentration Composite Map (in GeoTIFF format)

These Geotiff files are intended for use only during the anonymous peer-review process of the manuscript. For the source regions of Yangtze River, please refer to files with the prefix "CJY". As for the Qinghai-Tibet Plateau, we have only uploaded one year of data for review. We will upload all the Geotiff files upon acceptance of the manuscript. Please feel free to contact the email provided if you have any questions:<a href="mailto:jinlongli@stu.scu.edu.cn">jinlongli@stu.scu.edu.cn</a>.

opencc-by-4.0Aug 2022View details →

Differential algebra mappings of CR3BP periodic solutions

This dataset is made of twenty-three items containing polynomial mappings of families of periodic solutions of the circular restricted 3-body problem (CR3BP) [1], here the Earth-Moon and the Sun-(Earth-Moon) systems. Each file stores a list of differential algebra (DA) [2] maps representing these families with their associated domains of definition. The DA maps were computed using DA solving of two-point boundary value problem [3] and allow one to access initial conditions of solutions of the CR3BP by polynomial evaluation instead of heavy computations, provided the files containing the DA polynomials [4]. Each family is available with three different accuracies, also called tolerances. They are, with increasing accuracy, 1e-5, 1e-8, and 1e-10. The most accurate ones have higher loading and evaluation times and use more disk space but give better approximations of the families. The code DAHALOa_reader allows to read these files and can on GitHub: <a href="https://github.com/ThomasClb/DAHALOa_reader">ThomasClb/DAHALOa_reader (github.com)</a> References [1] V. Szebehely, ‘Theory of Orbit', Academic Press, 1967, pp. 7-41. DOI: <a href="https://doi.org/10.1016/B978-0-12-395732-0.50007-6">10.1016/B978-0-12-395732-0.50007-6</a> [2] R. Armellin, P. Di Lizia, et al., ’Asteroid close encounters characterization using differential algebra: the case of Apophis', Celestial Mechanics and Dynamical Astronomy, Vol. 107, No. 4, 2010, pp. 451-470. DOI: <a href="https://doi.org/10.1007/s10569-010-9283-5">10.1007/s10569-010-9283-5</a> [3] P. Di Lizia, R. Armellin, and M. Lavagna, 'Application of high order expansions of two-point boundary value problems to astrodynamics', Celestial Mechanics and Dynamical Astronomy, Vol. 102, No. 4, 2008, pp. 355-375. DOI: <a href="https://doi.org/10.1007/s10569-008-9170-5">10.1007/s10569-008-9170-5</a> [4] T. Caleb, M. Losacco, A. Fossà, R. Armellin, and S. Lizy-Destrez, 'Differential algebra methods applied to continuous  abacus generation and bifurcation detection: application to periodic families of the Earth–Moon system', Nonlinear dynamics, Vol. 111, 2023, pp. 9721-9740. DOI: <a href="https://doi.org/10.1007/s11071-023-08375-0">10.1007/s11071-023-08375-0</a>

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Data from: A brain-wide analysis maps structural evolution to distinct anatomical modules

Brain anatomy is highly variable and it is widely accepted that anatomical variation impacts brain function and ultimately behavior. The structural complexity of the brain, including differences in volume and shape, presents an enormous barrier to define how variability underlies differences in function. In this study, we sought to investigate the evolution of brain anatomy in relation to brain region volume and shape across the brain of a single species with variable genetic and anatomical morphs. We generated a high-resolution brain atlas for the blind Mexican cavefish and coupled the atlas with automated computational tools to directly assess variability in brain region shape and volume across all populations. We measured the volume and shape of every neuroanatomical region of the brain and assessed correlations between anatomical regions in surface fish, cavefish, and surface to cave F2 hybrids, whose phenotypes span the range of surface to cave. We find that dorsal regions of the brain are contracted in cavefish, while ventral regions have expanded. This trend is true for both volume and shape, suggesting that these two parameters share developmental mechanisms necessary for remodeling the entire brain. Given the high conservation of brain anatomy and function among vertebrate species, we expect these data to reveal generalized principles of brain evolution and show that Astyanax provides a system for functionally determining basic principles of brain evolution by utilizing the independent genetic diversity of different morphs, to test how genes influence early patterning events to drive brain-wide anatomical evolution.

opencc-zeroApr 2023View details →

Dataset for the BDD systematic mapping study

This is the data for the research article titled "Behaviour Driven Development: A Systematic Mapping Study", which has been accepted for publication by The Journal of Systems and Software.

opencc-by-4.0Dec 2022View details →

Map of the global wildland-urban interface

The wildland-urban interface (WUI) is where buildings and wildland vegetation meet or intermingle. It is where human-environmental conflicts and risks are concentrated, including the loss of houses and lives to wildfire, habitat loss and fragmentation, and the spread of zoonotic diseases. However, a global analysis of the WUI has been lacking. This dataset features a global, 10 m resolution map of the wildland-urban interface that was developed in a recent study by the authors of this dataset (see corresponding publication). Temporal extent The data contains data representative for ca. 2020. Data format and units The data are organized in tiles of 100 km x 100 km and follow the EQUI7 tiling grid and projection system. The images are compressed GeoTiff files (*.tif). There is a mosaic in GDAL Virtual format (*.vrt), which can readily be opened in most Geographic Information Systems. Please consider the generation of image pyramids before using *.vrt files. The raster dataset contains Wildland-urban interface (WUI) data (one layer), 10 m spatial resolution, 8 discrete classes: 1 - Forest/Shrubland/Wetland-dominated Intermix WU 2 - Forest/Shrubland/Wetland-dominated Interface WUI 3 - Grassland-dominated Intermix WUI 4 - Grassland -dominated Interface WUI 5 - Non-WUI: Forest/Shrub/Wetland-dominated 6 - Non-WUI: Grassland-dominated 7 - Non-WUI: Urban 8 - Non-WUI: Other In addition, the data contain tabular data on WUI area, population and biomass in the WUI, as well as wildfire area and people affected by wildfire in the WUI per world region, country, subnational administrative unit and biome. The data also contain the key algorithm for WUI mapping (also accessible here: https://github.com/franzschug/global_wildland_urban_interface). Further information For further information, please see the publication or contact Franz Schug (fschug@wisc.edu). Visit the website of SILVIS lab, University of Wisconsin-Madison (http://silvis.forest.wisc.edu/globalwui) to learn more about the Wildland-Urban Interface. The data can be interactively visualizes in a web viewer <a href="https://geoserver.silvis.forest.wisc.edu/geodata/fast/globalwui/">here.</a> Corresponding publication Schug, Franz*; Bar-Massada, Avi; Carlson, Amanda R.; Cox, Heather; Hawbaker, Todd J.; Helmers, David; Hostert, Patrick; Kaim, Dominik; Kasraee, Neda K.; Martinuzzi, Sebastián; Mockrin, Miranda H.; Pfoch, Kira A.; Radeloff, Volker C. The global wildland-urban interface, DOI: 10.1038/s41586-023-06320-0 Funding This research was funded by the NASA Land Cover and Land Use Change Program under agreement 80NSSC21K0310.

Remotely Sensed Paddy Rice Map of South Korea (2017-2021)

This dataset includes paddy rice maps in South Korea from 2017 to 2021 with 10 m resolution, which was produced by analyzing time-series Sentinel-1 images with recurrent U-Net deep learning architecture. The paddy rice maps are a product of deep learning model predictions and DO NOT represent ground truth information. The detailed algorithm for producing the dataset can be found in the following paper: <a href="https://doi.org/10.1080/15481603.2023.2206539">https://doi.org/10.1080/15481603.2023.2206539</a> The used modeling architecture is indicated by "RU-net 3" in the paper, and the consisting products in the dataset is as follows: <ul> <li>PR_in_[Year] : Probabiltiy of paddy rice cultivation area inside the paddy boundary (levee)</li> <li>PR_bd_[Year] : Probabiltiy of levee</li> <li>PR_in and PR_bd files have a scale factor vaule of 1,000,000.</li> <li>PR_bi_[Year] : Binary map of paddy rice, Due to the pixel size much larger than the levee width, the pixels labeled as levees inevitably include a large portion of the cultivation area. Therefore, binary map represent the sum of PR_in and PR_bd exceeding 0.5 threshold.</li> </ul> Please cite the paper when using this dataset. This work was supported by the International Research and Development Program of the National Research Foundation of Korea (NRF), funded by the Ministry of Science and ICT [2021K1A3A1A78097879], and partially supported by the European Commission under contract H2020-CALLISTO [101004152]

Replication Package for: Mapping Firms' Locations in Technological Space: A Topological Analysis of Patent Statistics

This replication package contains the data and the code to generate the paper’s main results, as well as the Online Appendix, for “Mapping Firms’ Locations in Technological Space: A Topological Analysis of Patent Statistics” by Emerson G. Escolar, Yasuaki Hiraoka, Mitsuru Igami, and Yasin Ozcan (published in Research Policy, volume 52, issue 8, October 2023; full text available online at https://doi.org/10.1016/j.respol.2023.104821).

Short communication: Synchrotron-based elemental mapping of single grains to investigate variable infrared-radiofluorescence emissions [Data set]

This dataset accompanies a research paper in the journal Geochronology (<a href="https://doi.org/10.5194/gchron-6-77-2024">https://doi.org/10.5194/gchron-6-77-2024</a>). It contains the raw output of micro-XRF measurements carried out at the 5-ID SRX beamline at the National Synchrotron Light Source II (NSLS-II) at Brookhaven National Laboratory, USA, on coarse K-feldspar grains. Additionally, the XRF intensity attributed to each element after spectral fitting is provided for elemental mapping. The dataset also includes the output from scanning electron microscope energy-dispersive X-ray spectroscopy (SEM-EDS) measurements on coarse K-feldspar grains of two samples taken at Archéosciences Bordeaux, France.

opencc-by-4.0Dec 2022View details →

Linkage maps and genotype data of strawberry produced with skim-sequencing data

The following set of files contain the results and scripts to produce those results, described in Chapter 5 of the PhD thesis of Alejandro Thérèse Navarro, entitled "How to map a million markers: linkage mapping of skim-sequencing data in strawberry". In this study, a large dataset of markers produced by whole genome resequecning of a strawberry (Fragaria x ananassa) biparental population are used to generate linkage maps. To that end the software <a href="https://github.com/Alethere/SmoothDescent">Smooth Descent</a> is used, since it is oriented to obtaining linkage maps in usin low quality (error-prone) genotype data. With this methodology we were able to produce a linkage map of 27 out of 28 chromosomes of strawberry which containing 1.85M markers in ~2400 unique genetic mpositions. We also compare this map with a linkage map produced using SNP array data and with the genome sequence assembly "Camarosa".

Source data for paper "Mapping disease regulatory circuits at cell-type resolution from single-cell multiomics data"

Sample-paired scRNA-seq and scATAC-seq data collected from human peripheral blood mononuclear cells with Staphylococcus aureus infection. ScATAC-seq data collected from human peripheral blood mononuclear cells with COVID-19 infection.

Automated mapping and classification of valleys beneath the Greenland Ice Sheet: Datasets

Valley morphology and classification: training dataset and full dataset for Greenland This dataset contains: <ul> <li>TrainingDataValleys.csv: A .csv file of the training dataset used to classify valleys in Greenland as 'fluvial' or 'glacial'. These valleys were extracted from the Copernicus 90 m global digital elevation model.</li> <li>GreenlandValleys.csv: A .csv file of the locations, morphometrics, and class of Greenland valleys identified in Operation IceBridge and CReSIS radio-echo sounding data. These valleys have been classified using a random forest model trained using the above training dataset.</li> </ul>

opencc-by-4.0Apr 2023View details →

Mapping the neuroethological signatures of pain, analgesia and recovery in mice

Mapping the neuroethological signatures of pain, analgesia and recovery in mice. Repository containing datasets obtained for M. Bohic, L Pattison, et al. 2023. Neuron.   Abstract Ongoing pain is driven by direct activation of pain-sensing neurons and neuroimmune mediated sensitization. These heightened pain states alter physiology, reduce motor function, and affect motivation to engage in normal behaviors. The complexity of the pain state has evaded a comprehensive definition, especially in nonverbal animals. Here in mice, we capture the physiological state of sensitized neurons and use computational tools to automatically map behavioral signatures of evoked and spontaneous displays of pain at different time points for both an acute model of paw inflammatory pain and a chronic model of knee joint pain. First, retrograde labeling coupled with electrophysiology of neurons innervating injury sites revealed key time points corresponding to peripheral sensitivity in multiple pain models. Next, we used high-speed videography combined with supervised and unsupervised machine learning tools to uncover sensory-evoked defensive coping postures, unique to each pain condition. Using 3D pose analytics inspired by natural language processing, we identify movement sequences that correspond to robust representations of ongoing pain states. With this new analytical framework, we find that commonly used analgesics do not return an animal’s behavior to a pre-injury state. Instead, animals adopt a novel set of spontaneous behaviors that are maintained even after most evoked behavioral features of pain have resolved. Together, these findings reveal previously unidentified neuroethological signatures of pain and analgesia at timescales when inflammation induces heightened pain states and during recovery.

Drawing the Boundaries Around Borderline Personality Disorder: A Science Mapping Study

Objective: The objective of this study was to conduct a bibliometric investigation of borderline personality disorder (BPD) including performance analysis, science mapping, and network visualization. Methods: Publications relating to BPD were retrieved from the Web of Science™ by entering the term “borderline personality disorder(all-fields)” and analyzed with the Bibliometrix.. Results: A total of 10,368 documents on BPD were published from 1980 to 2022. Publication volume increased by an average annual rate of 13.7%. The total number of citations of the period was 361,184, with an average citation per document of 34.8. Articles in “medical” journals tended to cite articles in the “medical” ones, while those in “psychological” journals did the same with their “psychological” counterparts. The list of the most cited articles includes predominantly studies on several modalities of psychotherapy for BPD. Articles about psychotherapy formed a separate co-citation cluster from the main body of publications and authors with stronger research imprinting on cognitive, dialectical, and mentalization- and schema-based psychotherapies formed a separate cluster from other authors, possibly reflecting the pivotal role played by psychotherapies in the treatment of BPD.  European countries collaborated among themselves, while the USA stood relatively apart. German, Dutch, and Swiss institutions, headed by the Heidelberg University, cooperated mainly among themselves while the USA ones formed separated networks around Harvard University. Conclusions: Our results indicate that research on BPD is a conceptually and thematically heterogeneous, geographically and institutionally diversified, integrated collaborative enterprise.

Spatial Mapping and Host Linking of Mobile Genetic Elements in Complex Microbiomes - Visualizing phage infection

We staged infections at four multiplicities of infection (MOI 0, 0.01, 0.1, and 1), and took snapshots every ten minutes over a 40-minute period. We designed FISH probes targeting the non-coding strand of the gp34 gene, which encodes a tail fiber protein and quantified cells with 5 or more MGE spots, less than 5 spots, and no spots

[ELMI2023] BioImage Town (BIT) FAIR Data Metro Map

Figures created collaboratively by the presenters of the Data Management and Analysis session of ELMI2023 (https://elmi2023.eu/) for their presentations. They represent an idealized metro through which data ("the passengers") travel between various solutions ("the stops") within bioimaging ("BioImage Town"), but also connecting to IT solutions, metadata, and other areas, though of course the real situation is much more complicated. Working together, we should be able to the improve the number of easy-to-use, performant, and complete solutions through BioImage Town for the benefit of the community.

Mapping User Attention: Filtering and Visualizing Relevant UI Components in Screenshots based on Gaze Fixations

These data correspond to the set of problems used for the evaluation of the proposal What Are You Gazing At? An Approach to Use Eye-tracking for Robotic Process Automation. Each problem consists of a set of 10 screenshots with the same look and feel but different data values for those values that can be entered/modify by the user. Each problem has its associated gaze fixation data. In each of the problems there is a key UI element that primarily attracts the attention of the user. The evaluation is based on a set of images which resemble realistic screenshots of activities in the administrative domain. More precisely, 5 different set of screenshots (S) are generated, each of them with a different level of complexity. Complexity is measured in terms of the number of UI elements per screenshot. The sets are: <ul> <li>S1 Mockup-based email view. Represents the activity of viewing an email to check if it contains an attachment. In this case, the key UI element that receives the attention is the attachment inside the email.</li> <li>S2 Mockup-based CRM user details. Represents a user's detail viewing activity within a Client Relationship Management (CRM) platform. The key UI element is the checkbox that indicates if the user has all his invoices paid.</li> <li>S3 Real screenshot email view. Analogous to S1 but with real screenshots. It represents the activity of viewing an e-mail to check if it contains an attachment. In this case, the key UI element to which attention is paid is the attachment contained in the e-mail.</li> <li>S4 Real screenshot CRM user details. Analogous to S2 but with real screenshots. It represents a user's detail viewing activity within a CRM platform. The key UI element is the checkbox indicating whether the user has all their invoices paid.</li> <li>S5 Real screenshot CRM user details. Represents the split-screen display of two applications. On the left side a pdf viewer, showing a covid vaccination certificate. And on the right side a human resources management system (basic recreation of real system for privacy reasons). In this one the detail of the employee to whom the certificate of the left side corresponds is visualized. These screenshots, having two applications, have two key UI elements. In the pdf viewer it is the name of the certificate holder and in the human resources management system it is the name of the employee whose detail view is being displayed. The activity being carried out is the verification that the covid certificate received corresponds to that of an employee.</li> </ul> Two types of filters based on the gaze fixation data are applied to these sets of screenshots: Pre-filtering and Post-filtering, corresponding to applying the filtering before and after detecting UI components in the screenshots, respectively. The structure of the data packages is divided in two folders input and output. The input folder is organized as follows: input/ <ul> <li>screenshots/: corresponds to the screenshots. The sets of screenshots are easily identifiable, they are named following the pattern: SX_screenshot_DDDD.jpeg. Where X indicates to which of the set of screenshots described in the previous list it belongs, and DDDD represents a unique identifier for each screenshot. Each group consists of 10 screenshots, being 50 in total.</li> <li>fixation.json: It is a JSON file that contains a key associated with each of the screenshots. For each screenshot, it contains a "fixation_points" key where information about the fixations that have occurred on the screenshot is stored. Here's an example: <pre><code> "S5_screenshot_0050.jpeg": { "fixation_points": { "334.25#497.166666666667": { "#events": 6, "start_index": 33224, "ms_start": 553962.1467, "ms_end": 554061.9899, "duration": 99.8432000001194, "imotions_dispersion": 0.300325967868111, "last_index": 33229, "dispersion": 14.044275227531914 }, "1258.80769230769#507.576923076923": { "#events": 13, "start_index": 33234, "ms_start": 554128.5427, "ms_end": 554345.3595, ...</code></pre> </li> </ul> The output folder is organized in three subfolders, the first one containing the information of the non-filtered screenshots (i.e. without having applied to them any filtering or processing), and the next two with the information resulting from pre-filtering and post-filtering. output/ <ul> <li>non-filter/ <ul> <li>borders/: screenshots with highlighted borders of all UI components detected in it.</li> <li>components_json/: a collection of JSON files with the same name as the screenshot, containing the "img_shape" key with a list of the screen resolution and the number of layers the image has: [1080, 1920, 3], and the "compos" key with a list of all UI components representing the Screen Object Model.  </li> </ul> </li> <li>pre-filter/ and post-filter/ <ul> <li>borders/: screenshots with the borders of the relevant UI components. In the case of prefiltering, the detection of components is only performed on the parts of the screenshot that have received attention. In postfiltering, the complete screenshot is shown, with only the borders of the relevant UI components highlighted.</li> <li>components_json/: a collection of JSON files with the same name as the screenshot is included, containing the following keys: <ul> <li>"img_shape": A list representing the screen resolution and the number of layers in the image, e.g., [1080, 1920, 3].</li> <li>"compos": A list of all UI components representing the Screen Object Model (SOM). During post-filtering, each UI component is augmented with an additional property called "relevant." If this property is set to true, it indicates that the respective UI component has received attention.</li> </ul> </li> <li>(pre)/(post)filter_attention_maps/: represent the attention maps. In the case of prefiltering, any surface of the screen that has not received attention will be shown in black. In the case of postfiltering, the areas of attention will be shown as red circles, and the UI components whose area intersects with the areas of attention by more than 25% will be shown in yellow.</li> </ul> </li> </ul> In conclusion, the described data package consists of sets of screenshots, accompanied by prefiltering and postfiltering filters using gaze fixation data, enabling the identification of relevant UI components. The organized data packages include input and output folders, where the output folder offers processed screenshots, UI component information, and attention maps. This resource provides valuable insights into user attention and interaction with UI elements on different types of scenarios.

Map-based stochastic simulation data of a transient Ekman boundary layer

Overview   A journal paper in Advances in Science and Research [1] details the numerical modeling approach used to create the data. Here, the model input files, the raw data, processed data, and plot scripts are provided that support the research. The code used here [2,3] is an extended version of the one-dimensional turbulence (ODT) model [4,5]. The current model implementation utilizes an adaptive grid that further increases numerical efficiency [6.7]. A truncated version of the adaptive ODT code of this work is described in [8] and publicly available free of charge in [9]. The theoretical foundation and numerical as well as experimental evidence for this work is given in [10,11,12,13], and the main motivation in [14]. The bash script makePlot.sh is the top-level driver and contains all additional information about the cases. Some other Details are provided by low-level README files. Python-3.8 is required to run the scripts. References [1]  M. Klein, and H. Schmidt. Capturing features of turbulent Ekman–Stokes boundary layers with a stochastic modeling approach. Adv. Sci. Res, 20, 55–64, https://doi.org/10.5194/asr-20-55-2023, 2023. [2] M. Klein, and H. Schmidt. Exploring stratification effects in stable Ekman boundary layers using a stochastic one-dimensional turbulence model, Adv. Sci. Res., 19, 117–136, https://doi.org/10.5194/asr-19-117-2022, 2022. [3] M. Klein, and H. Schmidt. A stochastic modeling strategy for intermittently unstable Ekman—Stokes boundary layers, Proc. Appl. Math. Mech., 20, e202000127, https://doi.org/10.1002/pamm.202000127, 2020. [4] A. R. Kerstein. One-dimensional turbulence: Model formulation and application to homogeneous turbulence, shear flows, and buoyant stratified flows, J. Fluid Mech., 392, 277–334, https://doi.org/10.1017/S0022112099005376, 1999. [5] A. R. Kerstein, and S. Wunsch. _Simulation of a stably stratified atmospheric boundary layer using one-dimensional turbulence, Boundary-Layer Meteorol., 118, 325–356, https://doi.org/10.1007/s10546-005-9004-x, 2006. [6] D. O. Lignell, A. R. Kerstein, G. Sun, and E. T. Monson. Mesh adaption for efficient multiscale implementation of one-dimensional turbulence, Theor. Comput. Fluid Dyn., 27, 273–295, https://doi.org/10.1007/s00162-012-0267-9, 2013. [7] D. O. Lignell V. B. Lansinger, J. Medina, M. Klein A. R. Kerstein, H. Schmmidt, M. Fistler, and M. Oevermann. One-dimensional turbulence modeling for cylindrical and spherical flows: model formulation and application, Theor. Comput. Fluid Dyn., 32, 495–520, https://doi.org/10.1007/s00162-018-0465-1, 2018. [8] V. B. Stephens, and  D. O. Lignell. One-dimensional turbulence (ODT): Computationally efficient modeling and simulation of turbulent flows, Software X, 13, 100641, https://doi.org/10.1016/j.softx.2020.100641, 2021. [9] BYU Ignite. Adaptive ODT source code, https://github.com/BYUignite/ODT. [10] S. Salon, and V. Armenio. A numerical investigation of the turbulent Stokes–Ekman bottom boundary layer, J. Fluid Mech., 684, 316–352, https://doi.org/10.1017/jfm.2011.303, 2011. [11] M. Klein, T. Seelig, M. V. Kurgansky, A. Ghasemi V., I. D. Borcia, A. Will, E. Schaller, C. Egbers, and U. Harlander. Inertial wave excitation and focusing in a liquid bounded by a frustum and a cylinder, J. Fluid Mech., 751, 255–297, https://doi.org/10.1017/jfm.2014.304, 2014. [12] A. Ghasemi, M. Klein, A. Will, and U. Harlander. Mean flow generation by an intermittently unstable boundary layer over a sloping wall, J. Fluid Mech., 853, 111–149, https://doi.org/10.1017/jfm.2018.552, 2018. [13] M. Vincze, N. Fenyvesi, M. Klein, J. Sommeria, S. Viboud, and Y. Ashkenazy. Evidence for wind-induced Ekman layer resonance based on rotating tank experiments, EPL, 125, 44001, https://doi.org/10.1209/0295-5075/125/44001, 2019. [14] L. S. Freire. Large-eddy simulation of the atmospheric boundary layer with near-wall resolved turbulence, Boundary-Layer Meteorol., 184, 25–43, https://doi.org/https://doi.org/10.1007/s10546-022-00702-z, 2022.