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190 results for “intrusions”
Everglades Saltwater Intrusion Marsh Surface Water Dissolved CO2 June 19th to 25th 2022
Dissolved CO2 (ppm) was measured in surface water at the Everglades saltwater intrusion marsh eddy covariance flux tower (US-EvM on AmeriFlux) for one week in June 2022. Minute resolution measurements were made using the CO2-LAMP (Blackstock et al., 2019).
The Salinity and phosphorus mesocosm experiment in freshwater sawgrass wetlands: Determining the trajectory and capacity of freshwater wetland ecosystems to recover carbon losses from saltwater intrusion (FCE LTER), Florida, USA from 2015 to 2018
In experimental wetland mesocosms located at Florida Bay Interagency Science Center, Key Largo, Florida, researchers continuously added salinity (approximately 6.9 g salt d-1) and phosphorus ( approximately 0.5 mg P d-1) to Cladium jamaicense peat monoliths from February 2015 to February 2017 and quantified changes in carbon partitioning. Several studies, focusing on the functional roles of marsh, soil, periphyton and microbe in the sawgrass-peat ecosystem, summarized detailed methodology and results (Wilson et al. 2019; Servais et al. 2019; Mazzei et al. in press). Briefly, salinity was increased (~10 ppt) and phosphorus was added (0.45 mg P d-1) to simulate four treatment effects (n = 24 plots): i) freshwater and no-added phosphorus, ii) freshwater and added phosphorus, iii) saltwater and no-added phosphorus, and iv) saltwater and added phosphorus. Upon the termination of manipulation study (early February 2017), containers holding water and peat-sawgrass cores were drained, rinsed, and refilled with only freshwater without any added nutrient and salt. Then, we experimentally restored freshwater to previous treatment and control mesocosms from February 2017 to June 2018 to examine the capacity of wetland ecosystems to recover carbon losses from saltwater intrusion. Note that FCE1226_Water_quality.csv summarizes water quality during both the manipulation and restoration study; however, all other files in the Dataset Title section only summarize results from the restoration study. Detailed methodology is provided below.
3D simulation salinity intrusion of Vembanad Lake using FVCOM
<p>This Animation was created for the purpose of presenting an oral presentation at CMLRE, Kochi (OSICON 19, 12th December 2019).</p> <p>The paper entitled - "An Integrated Hydrological and Hydrodynamic Model for the Vembanad Lake, South West Coast of India" </p>
Tagged original datasets for 'Genetically Optimized Massively Parallel Binary Neural Networks for Intrusion Detection Systems'
<p>Tagged, non-formatted, original datasets used in 'Genetically Optimized Massively Parallel Binary Neural Networks for Intrusion Detection Systems', T. Murovič, A. Trost.</p> <p>Available from the original authors:</p> <p>1. <a href="https://www.unsw.adfa.edu.au/unsw-canberra-cyber/cybersecurity/ADFA-NB15-Datasets/">https://www.unsw.adfa.edu.au/unsw-canberra-cyber/cybersecurity/ADFA-NB15-Datasets/</a> (UNWS-NB15 dataset)</p> <p>2. <a href="https://www.unb.ca/cic/datasets/nsl.html">https://www.unb.ca/cic/datasets/nsl.html</a> (NSL-KDD dataset)</p>
A comparative assessment of the dentoskeletal effects of clear aligners versus miniplate-supported posterior intrusion with fixed appliances in adult anterior open bite patients. A multi-centre, retrospective cohort study.
<p>In this retrospective study, the aim was to evaluate the dentoskeletal effects of clear aligner treatment (Invisalign®) versus miniplate-supported posterior intrusion (MSPI) in adults with anterior open bite.</p>
FIG. 1 in The worked bone industry and intrusive fauna associated with the prehistoric cave burials of Abri des Autours (Belgium)
FIG. 1. — Location of Abri des Autours and other Belgian sites mentioned in the text.
Non invasive and minimally intrusive blood pressure estimates
<p>Currently, health disorders related to Blood Pressure (BP) fluctuations are within the most prevalent and of higher social and economic impact in the world. A continuous and routinary monitoring of the BP can contribute to the early identification of risk factors, and consequently, would help to prevent potential cardiovascular diseases. <br> <br> BP measurement methods based on the cuff are of widespread use today. The monitoring based on this technology is intrusive and cannot be made continuously, which is of fundamental importance to diagnose Hypertension accurately. Due to the discomfort, inconvenience and intrusiveness of the cuff-based measurements of BP most people undergo monitoring only when they present symptoms of cardiovascular problems and a high proportion of them do not complete the monitoring protocol. <br> <br> In order to provide a less intrusive technology for non-invasive and continuous BP monitoring, many researchers aimed to estimate the BP from Pulse Waveforms (PW), recorded using plethysmography, ultrasound, and tonometry. Some BP estimation methods based on these technologies have been successfully implemented in commercial products. <br> <br> However, the BP estimation from PW is still an open research problem. The hemodynamic behavior of people is complex and highly variable within and between subjects. This makes the estimation of BP from PW very challenging from the mathematical and computational modeling perspectives. <br> <br> For this reason we provide a dataset from two healthy subjects. The experimental paradigm is explained in advance. Data were acquired by using the Finapres® NOVA which is a non-invasive continuous blood pressure monitor. <br> <br> The data contains the following columns: <br> <br> - Timeline of the acquisition.<br> - The PPG (Photoplethysmography) signal measured in the right hand.<br> - The PPG (Photoplethysmography) signal measured in the foot.<br> - The arterial pressure estimated by Finapres® NOVA.<br> - The ECG signal.<br> - The occurrence of the handgrip maneuver on the specific time instant.</p>
Experimental dataset referring to: Non-intrusive temperature measurements for transient freezing in laminar internal flow using laser induced fluorescence
<p>This data set corresponds to the paper 'Non-intrusive temperature measurements for transient freezing in laminar internal flow using laser induced fluorescence. Please cite this paper when using this data. </p><p>The following conditions are included (for both the inlet and the centre of the channel):</p><p>Re = 474, T_in,set = 0.5</p><p>Re = 474, T_in,set = 5.0</p><p>Re = 474, T_in,set = 10.0</p><p>Re = 474, T_in,set = 15.0</p><p>Each folder includes the original two-color LIF ratio-metric data and the temperature recordings of the cold-plate as well as the inlet, outlet temperatures and the flow rate (TData). The header for the recordings is included in the main dataset which may be used to navigate the columns and select the relevant data.</p><p> </p>
Circum-Antarctic data used in "Tipping point behaviour of ice-sheet grounding-zone melting due to ocean water intrusion" by Bradley and Hewitt
<p>The file 'Antarctica-data.mat' contains the following fields:</p><p>'x' [units: m] x position of grid points</p><p>'y' [units m] y position of grid points</p><p>'tf_max' [units: C] maximum thermal forcing from Adusumilli et al. 2020 (doi: https://doi.org/10.1038/s41561-020-0616-z)</p><p>'H' [units: m] ice thickness from Bedmachine V3</p><p>'B' [units: m] bed elevation from Bedmachine V3</p><p>'mask' [units: n/a] Bedmachine V3 mask</p><p>'isedge' [units: n/a] Logical array with 1 corresponding to edges of ice shelves and 0 otherwise</p><p>'isgl' [units: n/a] Logical array with 1 corresponding to grounding line points and 0 otherwise</p><p>'isfront' [units: n/a] Logical array with 1 corresponding to ice fronts and 0 otherwise</p><p>'vx' [units: m/a] Ice velocity in the x-direction from ITS_LIVE 240m mosaic</p><p>'vy' [units: m/a] Ice velocity in the y-direction from ITS_LIVE 240m mosaic</p>
Intrusive and Non-Intrusive Uncertainty Quantification Methodologies for Pyrolysis Modeling
<p>This repository contains python scripts and results for uncertainty analysis of Arrhenius equation with kinetic parameters as uncertain. The data set contains folders for each PMMA variant (1,2 and 3) used for uncertainty quantification (UQ) and 'Misc' folder containing miscellaneous files and scripts used in the study. </p> <p>Each PMMA variant folder has further sub-folders for the UQ methods implemented:</p> <ol> <li>Intrusive polynomial chaos (IPC)</li> <li>Monte Carlo (MC)</li> <li>Non-intrusive polynomial chaos (NIPC)</li> </ol> <p>Additionally convergence and comparison for the UQ methods is available in sub-folders of the same name respectively.</p> <p>The python file 'UoWu_noLatex.mplstyle' for plotting style used by us is attached to ease the rerunning of the scripts.</p>
Supplementary data for "Increasing risks of extreme salt intrusion events across European estuaries in a warming climate", published in Communications Earth & Environment
<p>This data repository contains python scripts and post-processed climate model and salt intrusion length data to reproduce figures in the paper below.</p> <p>====================</p> <p>Title: Increasing risks of extreme salt intrusion events across European estuaries in a warming climate (<a href="https://www.nature.com/articles/s43247-024-01225-w">Link to the full paper</a>)</p> <p>Author: Jiyong Lee, Bouke Biemond, Huib de Swart, and Henk A. Dijkstra</p> <p>Journal: Communications Earth & Environment</p> <p>Year: 2024</p> <p>Publisher: Nature</p> <p>====================</p>
Widespread seawater intrusions beneath the grounded ice of Thwaites Glacier, West Antarctica
<p>Warm water from the Southern Ocean has a dominant impact on the evolution of Antarctic glaciers and in turn on their contribution to sea level rise. Using a continuous time series of daily-repeat satellite synthetic-aperture radar interferometry data from the ICEYE constellation collected in March-June 2023, we document an ice grounding zone, or region of tidally-controlled migration of the transition boundary between grounded ice and ice afloat in the ocean, at the main trunk of Thwaites Glacier, West Antarctica, a strong contributor to sea level rise with an ice volume equivalent to a 0.6-m global sea level rise. The ice grounding zone is 6 km wide in the central part of Thwaites with shallow bed slopes, and 2 km wide along its flanks with steep basal slopes. We additionally detect irregular seawater intrusions, 5-10 cm in thickness, extending another 6 km upstream, at high tide, in a bed depression located beyond a bedrock ridge that impedes the glacier retreat. Seawater intrusions align well with regions predicted by the GlaDS subglacial water model to host a high-pressure distributed subglacial hydrology system in between lower-pressure subglacial channels. Pressurized seawater intrusions will induce vigorous melt of grounded ice over kilometers, making the glacier more vulnerable to ocean warming, and increasing the projections of ice mass loss. Kilometer-wide, widespread seawater intrusion beneath grounded ice may be the missing link between the rapid, past, and present changes in ice sheet mass and the slower changes replicated by ice sheet models. The dataset includes grounding line positions, all ICEYE radar interferograms and parameter files, files of tidal predictions and corrections for change in atmospheric pressure, and output products from the GlADS subglacial hydrology model.</p>
Supporting material for: Geostratigraphic mapping of the intrusive Valentine Domes on the Moon
<p>This dataset is the supporting information for the article called: Geostratigraphic mapping of the intrusive Valentine Domes on the Moon. It contains a QGIS project, the vector data, and the rastar data used to create the geostratigraphic maps of the zone.</p>
Collecting baleen whale blow samples by drone: a minimally intrusive tool for conservation genetics
<p>In coastal British Columbia, Canada, marine megafauna such as humpback whales (<em>Megaptera novaeangliae</em>) and fin whales (<em>Balaenoptera physalus velifera</em>) have been subject to a history of exploitation and near extirpation. While their populations have been in recovery, significant threats are posed by proposed natural resource ventures in this region, in addition to the compounding effects of increasingly severe marine heatwaves. Genetic tools play a vital role in informing conservation efforts, but the associated collection of tissue biopsy samples can be challenging for the investigators and disruptive to the ongoing behaviour of the targeted whales. Here we evaluate a minimally intrusive approach based on collecting exhaled breath condensate, or respiratory 'blow' samples, from baleen whales using an unoccupied aerial system (UAS), within Gitga'at First Nation territory for conservation genetics. Minimal behavioural responses to the sampling technique were observed, with no response detected 87% of the time (of 112 UAS deployments). DNA from whale blow (<em>n</em> = 88 samples) was extracted, and DNA profiles consisting of 10 nuclear microsatellite loci, sex identification, and mitochondrial (mt) DNA haplotypes, were constructed. An average of 7.5 microsatellite loci per individual were successfully genotyped. The success rates for mtDNA and sex assignment were 80% and 89% respectively. Thus, this minimally intrusive sampling method can be used to describe genetic diversity and generate genetic profiles for individual identification. The results of this research show the potential of UAS-collected whale blow for conservation genetics from a remote location.</p>
Scripts, figures and output for "Oxygen intrusions sustain aerobic nitrite oxidation in anoxic marine zones" by Pearse J. Buchanan & colleagues.
<p>Scripts for producing the visualisations, analysis and model results presented in the paper entitled "<em>Oxygen intrusions sustain </em><em>aerobic nitrite-oxidizing bacteria in anoxic </em><em>marine zones</em>" by Pearse James Buchanan & colleagues. </p> <p>Figures.tar holds the figures made with the python scripts <br>Chemostat_model.tar holds the python code required for running the chemostat model<br>Chemostat_output.tar holds the output of our experiments<br>OxicMAGS.txt and mumax_MAGS_gRodon.txt are required data files for fig5.py</p> <p>Other python scripts and figures seen in the full paper are held at https://doi.org/10.5281/zenodo.15139207 and were completed using jupyter notebooks on a memory intensive instance on the Expanse Super computer in San Diego. Please see those files for the remaining analysis.</p> <p><br>Contact pearse.buchanan@csiro.au or ezakem@carnegiescience.edu for any questions<br> </p> <p> </p>
HIRS Moon Intrusions and Model calculations
<p>The file "HIRS_moon_intrusions.csv" contains all 123 moon observations made with HIRS. The columns are:<br> ['Satellite', 'Version', 'Timestamp', 'Phase[deg]', 'Ang_diam[deg]',<br> 'Lat[deg]', 'Lon[deg]', 'Alt[km]', 'Dist[au]', 'Rad_[MJy/sr]_CH1',<br> 'Rad_err[MJy/sr]_CH1', 'Tb_[K]_CH1', 'Tb_err[K]_CH1',<br> 'Rad_[MJy/sr]_CH2', 'Rad_err[MJy/sr]_CH2', 'Tb_[K]_CH2',<br> 'Tb_err[K]_CH2', 'Rad_[MJy/sr]_CH3', 'Rad_err[MJy/sr]_CH3',<br> 'Tb_[K]_CH3', 'Tb_err[K]_CH3', 'Rad_[MJy/sr]_CH4',<br> 'Rad_err[MJy/sr]_CH4', 'Tb_[K]_CH4', 'Tb_err[K]_CH4',<br> 'Rad_[MJy/sr]_CH5', 'Rad_err[MJy/sr]_CH5', 'Tb_[K]_CH5',<br> 'Tb_err[K]_CH5', 'Rad_[MJy/sr]_CH6', 'Rad_err[MJy/sr]_CH6',<br> 'Tb_[K]_CH6', 'Tb_err[K]_CH6', 'Rad_[MJy/sr]_CH7',<br> 'Rad_err[MJy/sr]_CH7', 'Tb_[K]_CH7', 'Tb_err[K]_CH7',<br> 'Rad_[MJy/sr]_CH8', 'Rad_err[MJy/sr]_CH8', 'Tb_[K]_CH8',<br> 'Tb_err[K]_CH8', 'Rad_[MJy/sr]_CH9', 'Rad_err[MJy/sr]_CH9',<br> 'Tb_[K]_CH9', 'Tb_err[K]_CH9', 'Rad_[MJy/sr]_CH10',<br> 'Rad_err[MJy/sr]_CH10', 'Tb_[K]_CH10', 'Tb_err[K]_CH10',<br> 'Rad_[MJy/sr]_CH11', 'Rad_err[MJy/sr]_CH11', 'Tb_[K]_CH11',<br> 'Tb_err[K]_CH11', 'Rad_[MJy/sr]_CH12', 'Rad_err[MJy/sr]_CH12',<br> 'Tb_[K]_CH12', 'Tb_err[K]_CH12', 'Rad_[MJy/sr]_CH13',<br> 'Rad_err[MJy/sr]_CH13', 'Tb_[K]_CH13', 'Tb_err[K]_CH13',<br> 'Rad_[MJy/sr]_CH14', 'Rad_err[MJy/sr]_CH14', 'Tb_[K]_CH14',<br> 'Tb_err[K]_CH14', 'Rad_[MJy/sr]_CH15', 'Rad_err[MJy/sr]_CH15',<br> 'Tb_[K]_CH15', 'Tb_err[K]_CH15', 'Rad_[MJy/sr]_CH16',<br> 'Rad_err[MJy/sr]_CH16', 'Tb_[K]_CH16', 'Tb_err[K]_CH16',<br> 'Rad_[MJy/sr]_CH17', 'Rad_err[MJy/sr]_CH17', 'Tb_[K]_CH17',<br> 'Tb_err[K]_CH17', 'Rad_[MJy/sr]_CH18', 'Rad_err[MJy/sr]_CH18',<br> 'Tb_[K]_CH18', 'Tb_err[K]_CH18', 'Rad_[MJy/sr]_CH19',<br> 'Rad_err[MJy/sr]_CH19', 'Tb_[K]_CH19', 'Tb_err[K]_CH19']<br> Each row is one observation.</p> <p>The file TPM_calculations.zip contains the corresponding model calculations, while each .txt file is one model calculation.</p>
Farm-Flow | AG-IoT Security: Intrusion Detection in Smart Agriculture Dataset
<div> <div> <p><strong>Introduction:</strong></p> <p>The "Farm-Flow" dataset was created to emulate real-world Agricultural Internet of Things (AG-IoT) systems, encompassing network attacks and data collection. Following comprehensive cleaning and processing, the "Farm-Flow" dataset comprises 532 MB of data with 1,310,000 instances, structured around "flows," which represent consecutive series of packets transmitted from a single source to a specific destination. The dataset demonstrates an intrusion detection accuracy of 92.67% and is intended to enhance the security of AG-IoT systems, safeguarding information such as crop health, weather patterns, and soil conditions</p> <p><strong>Captures:</strong></p> <p>The captures comprises three months of network traffic: August, September, and October of 2022. Each month is divided into folders, which categorize the network traffic. These folders contain numerous .pcap files, which have been divided into 5-second intervals. This segmentation is necessary because, as previously mentioned, flows aggregate packets, resulting in only one row of flow data for ongoing connections. To address this, a script was developed to segment the .pcap files into 5-second increments. This approach allows for the generation of multiple rows of flow connections, thereby providing more quantity of data for model training.</p> <p><strong>Dataset:</strong></p> <p>The dataset comprises 532 MB of data, encompassing 1,310,000 instances. These instances have been classified into eight distinct attack types and one category for normal traffic. The identified attacks include Arp Spoofing, BotNet DDoS, HTTP Flood, ICMP Flood, MQTT Flood, Port Scanning, TCP Flood, and UDP Flood. Among the data set, there are 27,458 instances of normal traffic and 1,282,429 instances of aggregated attack traffic.</p> <p><strong>Zip Folder:</strong></p> <p>The zip folder is structured into two main directories: Captures and Dataset. The Captures directory is organized by the month of capture and further categorized by network traffic type. The Datasets directory includes the Farm-Flow Dataset, alongside four additional datasets that have undergone pre-processing: the training and testing datasets for binary classification, and the training and testing datasets for multiclass classification. Additionally, there are further datasets categorized by month and type of network traffic.</p> <p><strong> Article Information:</strong></p> <p>The work involved in developing the Farm-Flow dataset is described in the following paper. Please cite the paper and the dataset when using the Farm-Flow dataset.</p> <blockquote> <p>Rafael Ferreira, Ivo Bispo, Carlos Rabadão, Leonel Santos, and Rogério Luís de C. Costa (2025). <em>Farm-flow dataset: Intrusion detection in smart agriculture based on network flows</em>, Computers and Electrical Engineering, Volume 121, 109892, DOI: <a href="https://doi.org/10.1016/j.compeleceng.2024.109892." target="_blank" rel="noopener"> 10.1016/j.compeleceng.2024.109892</a></p> </blockquote> </div> </div>
Data for: Seawater intrusions in the observed grounding zone of Petermann Glacier causes extensive retreat
<p>Understanding grounding line dynamics is critical for projecting glacier evolution and sea level rise. Recent observations from satellite radar interferometry reveal rapid grounding line migration forced by oceanic tides that are several kilometers larger than predicted by hydrostatic equilibrium alone, indicating that the transition from grounded to floating ice is more complex than previously thought. Recent studies suggest that seawater intrusions beneath grounded ice may play a role in glacier dynamics. Here, we investigate their impact on the evolution of Petermann Glacier, Greenland, using an ice sheet model. We compare the model results with observed changes in grounding line position, velocity, and ice elevation between 2010 and 2022. If we exclude seawater intrusions, the model requires anomalously high melt rates to replicate the retreat. Conversely, we match the observed retreat with 3-km-long seawater intrusions with a maximum ice shelf melt rate of 50~m/yr, consistent with observations. We also obtain more realistic glacier speedup and ice thinning when including seawater intrusions in the model. We conclude that seawater intrusions play a critical role in the dynamics of Petermann Glacier. Including them in glacier flow models will make glaciers more sensitive to ocean warming and increase projections of sea level rise.</p>
2012-2014 post-eruptive intrusions at El Hierro
<p>Matlab files with LOS and GNSS data used in the manuscript "Magma flow rates and temporal evolution of the 2012-2014 post-eruptive intrusions at El Hierro, Canary Islands", JGR Solid Earth, 2019.</p> <p>GNSS data show north, east, and up displacements, and their respective uncertainties, with the number of station.</p>
Experimental data generated on the thermal behaviour during the intrusion–extrusion of ZIF-8 with different salt solutions
<p>/* **********<br>/* This work is licensed under a Creative Commons Attribution 4.0 International License.<br>/* **********</p> <p>Open access to experimental data generated by the project Electro-Intrusion (101017858, Horizon 2020, European Union) along with the research on the thermal behaviour of hydrophobic porous materials to be used in intrusion-extrusion applications. Research pertaining to Task 3.1 (WP3).<br>Underlying data for the publication Bartolomé, L. et al. Tuning Wetting-Dewetting Thermomechanical Energy for Hydrophobic Nanopores via Preferential Intrusion. The Journal of Physical Chemistry Letters 2023, 15, 880-887. https://doi.org/10.1021/acs.jpclett.3c03330. Data related to Figures 1, 3 and 4 in the article.</p> <p>Dataset Identifier: 10.5281/zenodo.13927359 </p> <p>Contact person: Luis Bartolomé (CIC energiGUNE). ORCID: https://orcid.org/0000-0001-9649-1470</p> <p><br>The archive 'JPCL_Tuning.zip' contains 2 folders with 64 files in total.</p>
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OpenNeuro
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