cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.18419/darus-4770
title: Damped pendulum for nonlinear system identification - inputs are sampled from a multivariate-normal distribution - synthetically generated

description: &lt;h3&gt;Overview&lt;/h3&gt;
 &lt;p&gt;This dataset contains input-output data of a damped nonlinear pendulum that is actuated at the mounting point. The data was generated with &lt;code&gt;statesim&lt;/code&gt; [1], a python package for simulating linear and nonlinear ODEs, for the system &lt;code&gt;actuated pendulum&lt;/code&gt;. The configuration &lt;code&gt;.json&lt;/code&gt; files for the corresponding datasets (in-distribution and out-of-distribution) can be found in the respective folders. After creating the dataset, the files are stored in the &lt;code&gt;raw&lt;/code&gt; folder. Then, they are split into subsets for training, testing, and validation and can be found in the &lt;code&gt;processed&lt;/code&gt; folder; details about the splitting are found in the &lt;code&gt;config.json&lt;/code&gt; file.&lt;/p&gt;

&lt;p&gt; The dataset can be used to test system identification algorithms and methods that aim to identify nonlinear dynamics from input-output measurements. The training dataset is used to optimize the model parameters, the validation set for hyperparameter optimization, and the test set only for the final evaluation.&lt;/p&gt;

 &lt;p&gt;In [2], the authors used the same underlying dynamics to create their dataset but without damping terms.&lt;/p&gt;

&lt;h3&gt;Input generation&lt;/h3&gt;
Input trajectories are sampled from a multivariate-normal distribution.

&lt;h3&gt;Noise&lt;/h3&gt;
Gaussian white noise of approximately 30dB is added at the output.

&lt;h3&gt;Statistics&lt;/h3&gt;
&lt;p&gt;The input and output size is one.&lt;/p&gt;
&lt;ul&gt;
 &lt;li&gt;In-distribution data: 2 100 000 data points
 &lt;ul&gt;
 &lt;li&gt;Training: 10 000 trajectories of length 150&lt;/li&gt;
 &lt;li&gt;Validation: 2 000 trajectories of length 150&lt;/li&gt;
 &lt;li&gt;Test: 2 000 trajectories of length 150&lt;/li&gt;
 &lt;/ul&gt;
 &lt;/li&gt;
 &lt;li&gt;Out-of-distribution data: 7 times 100 000 data points
 &lt;p&gt;7 different datasets were only used for testing. Each dataset contains 200 trajectories of length 500.&lt;/p&gt;
 &lt;/li&gt;
&lt;/ul&gt;

 &lt;h3&gt;References&lt;/h3&gt;
 &lt;ol&gt;
 &lt;li&gt;Frank, D. &lt;em&gt;statesim&lt;/em&gt; [Computer software]. &lt;a href="https://github.com/Dany-L/statesim"&gt;https://github.com/Dany-L/statesim&lt;/a&gt;&lt;/li&gt;
 &lt;li&gt;Lu, L., Jin, P., Pang, G., Zhang, Z., & Karniadakis, G. E. (2021). &lt;a href="https://doi.org/10.1038/s42256-021-00302-5"&gt;Learning nonlinear operators via DeepONet based on the universal approximation theorem of operators.&lt;/a&gt; Nature machine intelligence, 3(3), 218-229.&lt;/li&gt;
 &lt;/ol&gt;
DOI: 10.18419/darus-4768
title: Coupled mass-spring-damper system for nonlinear system identification - actuated with random static inputs - synthetically generated

description: &lt;h3&gt;Overview&lt;/h3&gt;
 &lt;p&gt;This dataset contains input-output data of a coupled mass-spring-damper system with a nonlinear force profile. The data was generated with &lt;code&gt;statesim&lt;/code&gt; [1], a python package for simulating linear and nonlinear ODEs, for the system &lt;code&gt;coupled-msd&lt;/code&gt;. The configuration &lt;code&gt;.json&lt;/code&gt; files for the corresponding datasets (in-distribution and out-of-distribution) can be found in the respective folders. After creating the dataset, the files are stored in the &lt;code&gt;raw&lt;/code&gt; folder. Then, they are split into subsets for training, testing, and validation and can be found in the &lt;code&gt;processed&lt;/code&gt; folder; details about the splitting are found in the &lt;code&gt;config.json&lt;/code&gt; file.&lt;/p&gt;

&lt;p&gt; The dataset can be used to test system identification algorithms and methods that aim to identify nonlinear dynamics from input-output measurements. The training dataset is used to optimize the model parameters, the validation set for hyperparameter optimization, and the test set only for the final evaluation.&lt;/p&gt;

 &lt;p&gt;In [2], the authors use the same underlying dynamics to create their dataset.&lt;/p&gt;

&lt;h3&gt;Input generation&lt;/h3&gt;
Input trajectories are piecewise constant trajectories.

&lt;h3&gt;Noise&lt;/h3&gt;
Gaussian white noise of approximately 30dB is added at the output.

&lt;h3&gt;Statistics&lt;/h3&gt;
&lt;p&gt;The input and output size is one.&lt;/p&gt;
&lt;ul&gt;
 &lt;li&gt;In-distribution data: 1,500,000 data points
 &lt;ul&gt;
 &lt;li&gt;Training: 120 trajectories of length 7500&lt;/li&gt;
 &lt;li&gt;Validation: 20 trajectories of length 7500&lt;/li&gt;
 &lt;li&gt;Test: 60 trajectories of length 7500&lt;/li&gt;
 &lt;/ul&gt;
 &lt;/li&gt;
 &lt;li&gt;Out-of-distribution data: 10 times 3000 data points
 &lt;p&gt;10 different datasets were only used for testing. Each dataset contains 50 trajectories of length 6000.&lt;/p&gt;
 &lt;/li&gt;
&lt;/ul&gt;

 &lt;h3&gt;References&lt;/h3&gt;
 &lt;ol&gt;
 &lt;li&gt;Frank, D. &lt;em&gt;statesim&lt;/em&gt; [Computer software]. &lt;a href="https://github.com/Dany-L/statesim"&gt;https://github.com/Dany-L/statesim&lt;/a&gt;&lt;/li&gt;
 &lt;li&gt;Revay, M., Wang, R., & Manchester, I. R. (2020). &lt;a href="https://doi.org/10.1109/LCSYS.2020.3038221"&gt;A convex parameterization of robust recurrent neural networks&lt;/a&gt;. &lt;em&gt;IEEE Control Systems Letters&lt;/em&gt;, 5(4), 1363-1368.&lt;/li&gt;
 &lt;/ol&gt;
description: statesim, 0d819c7
DOI: 10.18419/darus-4769
title: Code for statesim - a python package to simulate dynamical systems from ordinary differential equations.

description: &lt;p&gt;Python package for simulating ordinary differential equations in state space form. See &lt;a href="https://darus.uni-stuttgart.de/file.xhtml?fileId=363843"&gt;README.md&lt;/a&gt; for details.&lt;/p&gt;
DOI: 10.15468/dl.t3p97f
title: Occurrence Download

description: A dataset containing 14 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is China",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "StateProvince is 内蒙古",
 "TaxonKey is Acer truncatum Bunge"
 ]
}

 The dataset includes 14 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000868-250225214225278/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5517/ccdc.csd.cc2ltx7l
title: CCDC 2408180: Experimental Crystal Structure Determination

description: Related Article: Xueqi Lan, Xiaoxia Gu, Yeting Zhang, Hong Hu, Zhengyi Shi, Chaohu Xiong, Xinye Huang, Binbin Song, Yuben Qiao, Weiguang Sun, Changxing Qi, Yonghui Zhang|2025|Bioorg.Chem.|156|108230|doi:10.1016/j.bioorg.2025.108230
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.15468/dl.xtp2v5
title: Occurrence Download

description: A dataset containing 12503 species occurrences available in GBIF matching the query:
{
 "and" : [
 "OccurrenceStatus is Present",
 "TaxonKey is Clitoria ternatea L."
 ]
}

 The dataset includes 12503 records from 363 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000869-250225214225278/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.vmw9uh
title: Occurrence Download

description: A dataset containing 608 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Sium sisarum L.",
 "HasCoordinate is true",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 608 records from 66 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000871-250225214225278/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.k9c64a
title: Occurrence Download

description: A dataset containing 80 species occurrences available in GBIF matching the query:
{
 "and" : [
 "OccurrenceStatus is Present",
 "TaxonKey is Euploea swainson (Godart, 1824)"
 ]
}

 The dataset includes 80 records from 20 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000873-250225214225278/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.34740/kaggle/dsv/10858627
title: Hacker News Cumulative Data
DOI: 10.15468/dl.c7s9px
title: Occurrence Download

description: A dataset containing 3030 species occurrences available in GBIF matching the query:
{
 "and" : [
 "OccurrenceStatus is Present",
 "TaxonKey is Graphium antiphates (Cramer, 1775)"
 ]
}

 The dataset includes 3030 records from 51 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000875-250225214225278/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.ntdusq
title: Occurrence Download

description: A dataset containing 1018793 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is United States of America",
 "HasCoordinate is true",
 "Year is 2010",
 "Month is November"
 ]
}

 The dataset includes 1018793 records from 310 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000850-250225214225278/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.7u8rdn
title: Occurrence Download

description: A dataset containing 1182 species occurrences available in GBIF matching the query:
{
 "and" : [
 "OccurrenceStatus is Present",
 "TaxonKey is Euploea phaenareta (Schaller, 1785)"
 ]
}

 The dataset includes 1182 records from 40 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000872-250225214225278/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.29ecdy
title: Occurrence Download

description: A dataset containing 6783 species occurrences available in GBIF matching the query:
{
 "and" : [
 "OccurrenceStatus is Present",
 "TaxonKey is Graphium doson (Felder & Felder, 1864)"
 ]
}

 The dataset includes 6783 records from 95 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000876-250225214225278/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.6084/m9.figshare.28492631
title: FCS files (R. nautus)

description: Raw data for "Rhinacanthus nasutus callus polyploidy".<br>(T1 = 0.00% colchicine, 24 h; T2 = 0.00% colchicine, 48 h; T3 = 0.05% colchicine, 24 h; T4 = 0.05% colchicine, 48 h; T5 = 1.00% colchicine, 24 h; T6 = 1.00% colchicine, 48 h; T7 = 0.20% colchicine, 24 h; T8 = 0.20% colchicine, 48 h)
DOI: 10.6084/m9.figshare.28492631.v1
title: Ploidy level of Rhinacanthus nasutus calli

description: The main objectives of this research were to study the effect of polyploidization on the phytochemical content and antioxidant activity of <i>R. nasutus</i> calli. To determine callus polyploidy, the relative DNA contents of each sample were examined using flow cytometry.
DOI: 10.5281/zenodo.14929463
title: Data for Fluorescence Lifetime Multiplexing with Environment-Sensitive Chemigenetic Probes

description: Data for the manuscript Fluorescence Lifetime Multiplexing with Environment-Sensitive Chemigenetic Probes
DOI: 10.5281/zenodo.14929464
title: Data for Fluorescence Lifetime Multiplexing with Environment-Sensitive Chemigenetic Probes

description: Data for the manuscript Fluorescence Lifetime Multiplexing with Environment-Sensitive Chemigenetic Probes
DOI: 10.5281/zenodo.14929504
title: 증명법
DOI: 10.5281/zenodo.14929505
title: 증명법
DOI: 10.5281/zenodo.14916368
title: XRD_analysis_ZnS_Ag

description: s_1_ZnS_Ag_1ml - s1- sample number, ZnS_Ag - sample name, 1 ml amount of silver

s_2_ZnS_Ag_2ml -s2- sample number, ZnS_Ag - sample name, 2ml amount of silver

s_3_ZnS_Ag_3ml - s3- sample number, ZnS_Ag - sample name, 3 ml amount of silver

s_4_ZnS_Ag_5ml - s4- sample number, ZnS_Ag - sample name, 4 ml amount of silver

s_5_ZnS_Ag_5ml - s5- sample number, ZnS_Ag - sample name, 5 ml amount of silver

s_6_ZnS_Ag_6ml - s6- sample number, ZnS_Ag - sample name, 6 ml amount of silver

s_7_ZnS_Ag_7ml - s7- sample number, ZnS_Ag - sample name, 7 ml amount of silver

s8_ZnS_Ag_8ml - s8- sample number, ZnS_Ag - sample name, 8 ml amount of silver

s9_ZnS_Ag_9ml -s9- sample number, ZnS_Ag - sample name, 9 ml amount of silver

s10_ZnS_Ag_10ml -s10- sample number, ZnS_Ag - sample name, 10 ml amount of silver

s11_ZnS - s11- sample number, ZnS-sample name

 
description: Funding: National Science Center Poland grand number: 2022/06/X/ST4/00176
DOI: 10.5281/zenodo.14916369
title: XRD_analysis_ZnS_Ag

description: s_1_ZnS_Ag_1ml - s1- sample number, ZnS_Ag - sample name, 1 ml amount of silver

s_2_ZnS_Ag_2ml -s2- sample number, ZnS_Ag - sample name, 2ml amount of silver

s_3_ZnS_Ag_3ml - s3- sample number, ZnS_Ag - sample name, 3 ml amount of silver

s_4_ZnS_Ag_5ml - s4- sample number, ZnS_Ag - sample name, 4 ml amount of silver

s_5_ZnS_Ag_5ml - s5- sample number, ZnS_Ag - sample name, 5 ml amount of silver

s_6_ZnS_Ag_6ml - s6- sample number, ZnS_Ag - sample name, 6 ml amount of silver

s_7_ZnS_Ag_7ml - s7- sample number, ZnS_Ag - sample name, 7 ml amount of silver

s8_ZnS_Ag_8ml - s8- sample number, ZnS_Ag - sample name, 8 ml amount of silver

s9_ZnS_Ag_9ml -s9- sample number, ZnS_Ag - sample name, 9 ml amount of silver

s10_ZnS_Ag_10ml -s10- sample number, ZnS_Ag - sample name, 10 ml amount of silver

s11_ZnS - s11- sample number, ZnS-sample name

s12_ZnS_Ag2_ml_after reaction -s12- sample number, ZnS_Ag - sample name, 2 ml amount of silver, sample after reaction
description: Funding: National Science Center Poland grand number: 2022/06/X/ST4/00176
DOI: 10.5281/zenodo.14929490
title: XRD_analysis_ZnS_Ag

description: s_1_ZnS_Ag_1ml - s1- sample number, ZnS_Ag - sample name, 1 ml amount of silver

s_2_ZnS_Ag_2ml -s2- sample number, ZnS_Ag - sample name, 2ml amount of silver

s_3_ZnS_Ag_3ml - s3- sample number, ZnS_Ag - sample name, 3 ml amount of silver

s_4_ZnS_Ag_5ml - s4- sample number, ZnS_Ag - sample name, 4 ml amount of silver

s_5_ZnS_Ag_5ml - s5- sample number, ZnS_Ag - sample name, 5 ml amount of silver

s_6_ZnS_Ag_6ml - s6- sample number, ZnS_Ag - sample name, 6 ml amount of silver

s_7_ZnS_Ag_7ml - s7- sample number, ZnS_Ag - sample name, 7 ml amount of silver

s8_ZnS_Ag_8ml - s8- sample number, ZnS_Ag - sample name, 8 ml amount of silver

s9_ZnS_Ag_9ml -s9- sample number, ZnS_Ag - sample name, 9 ml amount of silver

s10_ZnS_Ag_10ml -s10- sample number, ZnS_Ag - sample name, 10 ml amount of silver

s11_ZnS - s11- sample number, ZnS-sample name

 
description: Funding: National Science Center Poland grand number: 2022/06/X/ST4/00176
DOI: 10.60707/8trn-fc73
title: 40Ar/39Ar geochronology and thermochronology
DOI: 10.5281/zenodo.14925006
title: Dataset related to the Journal Article - Optimising the Design of a Hybrid Fuel Cell/Battery and Waste Heat Recovery System for Retrofitting Ship Power Generation

description: This dataset contains the data used to plot the graphs and create tables corresponding to the figure/table number in the published version of the paper (https://doi.org/10.3390/en18020288).
DOI: 10.5281/zenodo.14925007
title: Dataset related to the Journal Article - Optimising the Design of a Hybrid Fuel Cell/Battery and Waste Heat Recovery System for Retrofitting Ship Power Generation

description: This dataset contains the data used to plot the graphs and create tables corresponding to the figure/table number in the published version of the paper (https://doi.org/10.3390/en18020288).
DOI: 10.60707/xcjy-ym18
title: 40Ar/39Ar geochronology and thermochronology
DOI: 10.5281/zenodo.14929481
title: Dynamic vapour sorption (DVS) of pure mycelium skin

description: supplementary data for: Hýsek, Š., Jozífek, M., Němec, M., Hradecký, J., & Wimmer, R. (2024, září 25). Mycelium of medicinal mushrooms for production of mycelium-based bio-composites and its physical and mechanical properties. 12th International Medicinal Mushrooms Conference (IMMC12), Bari, Italy. Zenodo. https://doi.org/10.5281/zenodo.13839106

Raw and calculated data of dynamic vapour sorption of pure mycelium of G. lingzhi, G. sessile and P. ostreatus produced using liquid state fermentation. Lignin enrichment (0.5% and 2%) of liquid substrated used.
DOI: 10.5281/zenodo.14929482
title: Dynamic vapour sorption (DVS) of pure mycelium skin

description: supplementary data for: Hýsek, Š., Jozífek, M., Němec, M., Hradecký, J., & Wimmer, R. (2024, září 25). Mycelium of medicinal mushrooms for production of mycelium-based bio-composites and its physical and mechanical properties. 12th International Medicinal Mushrooms Conference (IMMC12), Bari, Italy. Zenodo. https://doi.org/10.5281/zenodo.13839106

Raw and calculated data of dynamic vapour sorption of pure mycelium of G. lingzhi, G. sessile and P. ostreatus produced using liquid state fermentation. Lignin enrichment (0.5% and 2%) of liquid substrated used.
DOI: 10.57680/asep.0617466
title: Dataset paper Amourphous DLC N

description: The data for the graphs are in the “*.csv” file format. The “*.tif” file format is used for the graphs, and the tables are shown in the “*.pdf” one. The description of the files is given in the “readme.txt” file.
DOI: 10.34740/kaggle/dsv/10858697
title: e-IPO Indonesia Data - Investment
DOI: 10.5281/zenodo.14925920
title: Testbeam dataset for characterisation of PicoAD proof-of-concept

description: Collection of all of the data used to obtain the results published in the following article: DOI: 10.1088/1748-0221/17/02/P02019.
DOI: 10.5281/zenodo.14925921
title: Testbeam dataset for characterisation of PicoAD proof-of-concept

description: Collection of all of the data used to obtain the results published in the following article: DOI: 10.1088/1748-0221/17/02/P02019.
DOI: 10.25375/uct.26942134
title: ESRG Hourly Demand Model v2025 by Province

description: Spreadsheet tool, which helps user construct hourly demand profiles to 2050 for South Africa, for a given set annual energy projections by sector and calibrated profiles by sector.Model calibrated to 2017 data and uses SATIMGE commit: 75aac7f718addb9766ae46e9702d95660b89271bIncludes some preliminary projections for distributed PV. This can be included or excluded by the user, as well as other onsite generators such as Sasol gas turbines, and exports.<br><br>This version was used to do a simple downscaling to Eskom Supply Areas (Provinces + Hydra), done here:<br>https://github.com/GregoryIreland/Demand-Spatialization-South-Africa<br>
DOI: 10.25375/uct.26942134.v4
title: ESRG Single Node Hourly Demand Model v2024

description: Spreadsheet tool, which helps user construct hourly demand profiles to 2050 for South Africa, for a given set annual energy projections by sector and calibrated profiles by sector.Model calibrated to 2017 data and uses SATIMGE commit: 75aac7f718addb9766ae46e9702d95660b89271bIncludes some preliminary projections for distributed PV. This can be included or excluded by the user, as well as other onsite generators such as Sasol gas turbines, and exports.<br><br>This version was used to do a simple downscaling to Eskom Supply Areas (Provinces + Hydra), done here:<br>https://github.com/GregoryIreland/Demand-Spatialization-South-Africa<br>
DOI: 10.15468/dl.fjm8e2
title: Occurrence Download

description: A dataset containing 3 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is Specimen",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Artocarpus altilis (Parkinson) Fosberg",
 "Year is 2010"
 ]
}

 The dataset includes 3 records from 2 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000878-250225214225278/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.6084/m9.figshare.25375180
title: <b>Diez-Gracia & Sánchez-García (2025).</b> Sample and chronology on the news gap research

description: This resource compiles the scientific literature available from 2010 to 2023 about the phenomenon of the news gap.This resource is part of the paper "Diez-Gracia & Sánchez-García (2025). “When digital audiences disregard the journalistic agenda: conceptualization and evolution of the news gap”. <i>Communication & Society, 34</i>(1)."
DOI: 10.6084/m9.figshare.28494134
title: Data for the article pepin et al. (<b>Evaluation of parasitic contamination and effects on estimates of mitochondrial enzymatic activities in infected fish livers</b>)

description: Parasites can impair host performance through various physiological processes, including alterations to host metabolism. Since mitochondria are responsible for cellular energy production, it is likely that disruptions in host cellular metabolism contribute to changes in metabolism at the organismal level. However, some studies investigating parasite-induced alteration in cellular metabolism have not taken the presence of parasites in the target tissues into account, potentially biasing results. It is therefore critical to confirm that the measured enzyme activities reflect those of the hosts rather than the parasites themselves. Here, we tested a parasite extraction protocol to evaluate the extent to which parasite contamination impacts estimates of cellular enzyme activities in hepatic tissues of wild pumpkinseed sunfish (<i>Lepomis gibbosus</i>) infected with bass tapeworm cestodes (<i>Proteocephalus ambloplitis</i>). We tested four treatments: uninfected livers, cleaned infected livers, infected livers (repopulated) and parasites alone. We then compared the activity of key metabolic enzymes among groups. PCR tests were used to assess parasitic contamination of samples after applying the parasite extraction protocol on hepatic tissue. Enzyme activities of cleaned livers and contaminated livers were similar despite PCR tests revealing contamination. The intensity of cestode infection also did not influence enzyme activity, which suggests that parasite presence in liver tissues does not impact the accuracy of the enzyme activity estimates. These results suggest that studying the organs of heavily parasitized individuals is possible. Nevertheless, we recommend that our cleaning protocol is applied to infected organs to avoid any perception of biases in highly infected individuals.