Find research datasets worth reusing

Fig. 2 in Size composition, monthly condition factor and morphometrics for fishery-dependent samples of Rioraja agassizi (Chondrichthyes: Rajidae), off Santos, Southeast Brazil

Fig. 2. Maps of Southeast Brazil, showing the fishing hauls by month, conducted by a total of eight fishing vessels. Symbols represent the fishing hauls from where samples of Rioraja agassizi were collected (dotted circles), or when this information was not available, the total hauls recorded by the skippers (crosses).

Fig. 6 in Size composition, monthly condition factor and morphometrics for fishery-dependent samples of Rioraja agassizi (Chondrichthyes: Rajidae), off Santos, Southeast Brazil

Fig. 6. Median condition factor by month (from March, 2005 to March, 2006) considering total (black line) and gutted weight (g) (grey line) for males (above) and females (below) of Rioraja agassizi. Vertical bars represent the data interval.

Fig. 4 in Size composition, monthly condition factor and morphometrics for fishery-dependent samples of Rioraja agassizi (Chondrichthyes: Rajidae), off Santos, Southeast Brazil

Fig. 4. Relationship of disc width (cm) as a dependent variable of total length (cm) for males (black symbols) and females (grey symbols) of Rioraja agassizi.

Fig. 1 in Size composition, monthly condition factor and morphometrics for fishery-dependent samples of Rioraja agassizi (Chondrichthyes: Rajidae), off Santos, Southeast Brazil

Fig. 1. Map of the study area, southeast Brazil, south-western Atlantic Ocean. Symbols represent all the fishing hauls from where samples of Rioraja agassizi were collected.

opencc-by-4.0Jul 2020View details →

Data supporting "Changes in human dorsal root ganglion neuron excitability from modulating Nav 1.8 conductance are non-linear and depend on the conductances of the delayed rectifier and M-type potassium currents: a simulation study"

Data and code supporting the article "Changes in human dorsal root ganglion neuron excitability from modulating Nav 1.8 conductance are non-linear and depend on the conductances of the delayed rectifier and M-type potassium currents: a simulation study".

opencc-zeroNov 2022View details →

Data for: Analytical transfer function for volcano deformation with T-dependent viscoelasticity

Rocks can modulate the triggering, duration, and style of volcanic eruptions. When heated, the host rocks surrounding a magmatic reservoir is typically considered as a viscoelastic material. The viscoelastic rheology (viscosity especially) is temperature dependent; however, the dynamics and consequence on surface deformation resulting from heterogeneous crustal temperature and viscosity around magmatic reservoirs have not been explored systematically. This dataset incorporates the parameters and numerical codes used for generating results in the manuscript 'History-dependent volcanic ground deformation from broad-spectrum viscoelastic rheology around magma reservoirs' submitted to GRL and authord by Yang Liao, Leif Karlstrom, and Brittany Erickson. The dataset consists of a README file detailing the data structure, a matlab .mat file that contains the parameters assumed in the magma chamber model, and several matlab program .m files that can be applied to the .mat file to generate results presented in the manuscript.

opencc-by-4.0Dec 2022View details →

Carbohydrate vitrification in aerosolized saliva is associated with the humidity-dependent infectious potential of airborne coronavirus - Datasets

Data includes: - WIBS files for each individual chamber run - RT-qPCR results - TCID50 results - Spreadsheet calculations - MOUDI results

opencc-by-4.0Dec 2021View details →

Dynamic analysis of pathogenesis and a suppression function of TREM2-dependent macrophages in skin fibrosis

Systemic sclerosis (SSc) is a chronic and incurable autoimmune disease with high mortality rates, and fibrosis is the distinguishing hallmark in the pathogenesis. Identification of the precise, time dependent composition of stromal and immune cells may provide clues for the establishment of new biomarkers and therapeutic approaches targeting SSc fibrosis. Here, the temporal dynamics of pathological process in a mouse model of skin fibrosis is investigated using single-cell RNA-sequencing (scRNA-seq).  we collected skin single cell suspensions for transcriptome profiling by scRNA-seq from four time points after BLM-treatment (day 3, 7, 14, and 28) and untreated control skin (day 0) with on average three replicate mice per time point, and repeated once at each time point.{mouse_SSc_scRNAseq_day0_sample1_B1_1, mouse_SSc_scRNAseq_day3_sample1_B2_1, mouse_SSc_scRNAseq_day3_sample2_B2_2, mouse_SSc_scRNAseq_day7_sample1_B3_1, mouse_SSc_scRNAseq_day7_sample2_B3_2, mouse_SSc_scRNAseq_day14_sample1_B4_1, mouse_SSc_scRNAseq_day14_sample2_B4_2, mouse_SSc_scRNAseq_day28_sample1_B5_1, mouse_SSc_scRNAseq_day28_sample2_B5_2}

opencc-by-4.0Apr 2022View details →

Substrate stiffness reduces particle uptake by epithelial cells and macrophages in a size-dependent manner through mechanoregulation

Cells continuously exert forces on their environment and respond to changes in mechanical forces by altering their behavior. Many pathologies such as cancer and fibrosis are hallmarked by dysregulation in the extracellular matrix, driving aberrant behavior through mechanotransduction pathways. We demonstrate that substrate stiffness can be used to regulate cellular endocytosis of particles in a size-dependent fashion. Culture of A549 epithelial cells and J774A.1 macrophages on polystyrene/glass (stiff) and polydimethylsiloxane (soft) substrates indicated that particle uptake is increased up to six times for A549 and two times for macrophages when cells are grown in softer environments. Furthermore, we altered surface characteristics through the attachment of submicron-sized particles as a method to locally engineer substrate stiffness and topography. To investigate the biomechanical changes which occurred within adherent epithelial cells, i.e. characterization of A549 cell spreading and focal adhesion maturation. Consequently, decreasing substrate rigidity and particle-based topography lead to a reduction of focal adhesion size. Moreover, expression levels of Yes-associated protein were found to correlate with the degree of particle endocytosis. A thorough appreciation of the mechanical cues may lead to improved solutions to optimize nanomedicine approaches for treatment of cancer and other diseases with abnormal mechanosignaling.

opencc-by-4.0May 2022View details →

Dataset related to: Shiga Toxin 2 Triggers C3a-Dependent Glomerular and Tubular Injury through Mitochondrial Dysfunction in Hemolytic Uremic Syndrome

The files contain all the dataset included in the manuscript, divided by figure in each tab.   Abstract Shiga toxin (Stx)-producing Escherichia coli is the predominant offending agent of post-diarrheal hemolytic uremic syndrome (HUS), a rare disorder of microvascular thrombosis and acute kidney injury possibly leading to long-term renal sequelae. We previously showed that C3a has a critical role in the development of glomerular damage in experimental HUS. Based on the evidence that activation of C3a/C3a receptor (C3aR) signaling induces mitochondrial dysregulation and cell injury, here we investigated whether C3a caused podocyte and tubular injury through induction of mitochondrial dysfunction in a mouse model of HUS. Mice coinjected with Stx2/LPS exhibited glomerular podocyte and tubular C3 deposits and C3aR overexpression associated with cell damage, which were limited by C3aR antagonist treatment. C3a promoted renal injury by affecting mitochondrial wellness as demonstrated by data showing that C3aR blockade reduced mitochondrial ultrastructural abnormalities and preserved mitochondrial mass and energy production. In cultured podocytes and tubular cells, C3a caused altered mitochondrial fragmentation and distribution, and reduced anti-oxidant SOD2 activity. Stx2 potentiated the responsiveness of renal cells to the detrimental effects of C3a through increased C3aR protein expression. These results indicate that C3aR may represent a novel target in Stx-associated HUS for the preservation of renal cell integrity through the maintenance of mitochondrial function.

opencc-by-4.0Oct 2022View details →

Use of Time Dependent Data in Bayesian Global 21cm Foreground and Signal Modelling (supplementary data)

These are the posterior files, foreground simulation data sets and chromaticity factor values used to produce the results for <a href="https://arxiv.org/abs/2210.04707">arXiv:2210.04707</a>.   A plotting script to reproduce key figures is included. Software used: <ul> <li><a href="https://github.com/PolyChord/PolyChordLite/tree/839292290a7747dbee82933bb9f7f955ac45c3ca">PolyChord</a></li> <li><a href="https://github.com/williamjameshandley/fgivenx">fgivenx</a></li> </ul>

opencc-by-4.0Oct 2022View details →

Dataset related to: Low Nephron Number Induced by Maternal Protein Restriction Is Prevented by Nicotinamide Riboside Supplementation Depending on Sirtuin 3 Activation

The files contain all the dataset included in the manuscript divided by figures. For each figure, individual tabs indicate data from different figure panels.   Abstract A reduced nephron number at birth, due to critical gestational conditions, including maternal malnutrition, is associated with the risk of developing hypertension and chronic kidney disease in adulthood. No interventions are currently available to augment nephron number. We have recently shown that sirtuin 3 (SIRT3) has an important role in dictating proper nephron endowment. The present study explored whether SIRT3 stimulation, by means of supplementation with nicotinamide riboside (NR), a precursor of the SIRT3 co-substrate nicotinamide adenine dinucleotide (NAD+), was able to improve nephron number in a murine model of a low protein (LP) diet. Our findings show that reduced nephron number in newborn mice (day 1) born to mothers fed a LP diet was associated with impaired renal SIRT3 expression, which was restored through supplementation with NR. Glomerular podocyte density, as well as the rarefaction of renal capillaries, also improved through NR administration. In mechanistic terms, the restoration of SIRT3 expression through NR was mediated by the induction of proliferator-activated receptor γ (PPARγ) coactivator-1α (PGC-1α). Moreover, NR restored SIRT3 activity, as shown by the reduction of the acetylation of optic atrophy 1 (OPA1) and superoxide dismutase 2 (SOD2), which resulted in improved mitochondrial morphology and protection against oxidative damage in mice born to mothers fed the LP diet. Our results provide evidence that it is feasible to prevent nephron mass shortage at birth through SIRT3 boosting during nephrogenesis, thus providing a therapeutic option to possibly limit the long-term sequelae of reduced nephron number in adulthood.

opencc-zeroDec 2021View details →

Scale-dependent diversity-biomass relationships can be driven by tree mycorrhizal association and soil fertility

Diversity–biomass relationships (DBRs) often vary with spatial scale in terrestrial ecosystems, but the mechanisms driving these scale-dependent patterns remain unclear, especially for highly heterogeneous forest ecosystems. This study explores how mutualistic associations between trees and different mycorrhizal fungi (i.e., arbuscular mycorrhizal (AM) vs. ectomycorrhizal (EM) association) modulate scale-dependent DBRs. We hypothesized that in soil-heterogeneous forests with a mixture of AM and EM tree species, (i) AM and EM tree species respond in contrasting ways (i.e., positively vs. negatively respectively) to increasing soil fertility, (ii) AM tree dominance contributes to higher tree diversity and EM tree dominance contributes to greater standing biomass and that as a result, (iii) mycorrhizal associations exert an overall negative effect on DBRs across spatial scales. To empirically test these hypotheses, we collected detailed tree distribution and soil information (nitrogen, phosphorus, organic matter, pH, etc.) from seven temperate and subtropical AM-EM mixed forest mega-plots (16–50 ha). Using spatial codispersion null model and structural equation modeling, we identified the relationships among AM or EM tree dominance, soil fertility, tree species diversity and biomass, and thus DBRs across 0.01–1 ha scales. We found first evidence overall supporting the above three hypotheses in these AM-EM mixed forests: (i) In most forests, with increasing soil fertility tree communities changed from EM-dominated to AM-dominated. (ii) Increasing AM tree dominance had an overall positive effect on tree diversity and a negative effect on biomass, even after controlling for soil fertility and number of trees. Together, (iii) the changes in mycorrhizal dominance along soil fertility gradients weakened the positive DBR observed at 0.01–0.04 ha scales in nearly all forests and drove negative DBRs at 0.25–1 ha scales in four out of seven forests. Hence, this study highlights a soil-related mycorrhizal dominance mechanism that could partly explain why in many natural forests, biodiversity-ecosystem functioning (BEF) relationships shift from positive to negative with increasing spatial scale.

opencc-by-4.0Jan 2023View details →

Microbiome of domestic water in rainwater-harvesting dependent Carriacou, Grenada - Water_aCCSIS Project

Data files for the manuscript "The microbiome of domestic water in the rainwater harvesting-dependent island community of Carriacou, Grenada in the southern Caribbean"

opencc-zeroJan 2023View details →

Computational analyses of dynamic visual courtship display reveal diet-dependent and plastic male signaling in Rabidosa rabida wolf spiders

It has long been a challenge to quantify the variation in dynamic motions to understand how those displays function in animal communication. The traditional approach is dependent on labor-intensive manual identification/annotation by experts. However, the recent progress in computational techniques provides researchers with toolsets for rapid, objective, and reproducible quantification of dynamic visual displays. In the present study, we investigated the effects of diet manipulation on dynamic visual components of male courtship displays of Rabidosa rabida wolf spiders using machine learning algorithms. Our results suggest that (i) the computational approach can provide an insight into the variation in the dynamic visual display between high- and low-diet males which is not clearly shown with the traditional approach and (ii) males may plastically alter their courtship display according to the body size of females they encounter. Through the present study, we add an example of the utilization of recent computational techniques for understanding the evolution of animal behaviors.

opencc-zeroJan 2023View details →

Data for: Can we ignore trait-dependent colonization and diversification in island biogeography?

The application of state-dependent speciation and extinction (SSE) models to phylogenetic trees has shown an important role for traits in diversification. However, this role remains comparatively unexplored on islands, which can include multiple independent clades resulting from different colonization events. To explore whether assuming no dependence on traits leads to bias in inference on island dynamics, we extend an island biodiversity model, DAISIE (Dynamic Assembly of Islands through Speciation, Immigration and Extinction) to include trait-dependent diversification simulations, and evaluate the robustness of the inference model which ignores this trait-dependence. Our results indicate that when the differences between colonization, extinction and speciation rates between trait states are moderate, the model shows negligible error for a variety of island diversity metrics, suggesting that island diversity dynamics can be accurately estimated without the need to explicitly model trait dependence. We conclude that for many biologically realistic scenarios with trait-dependent diversification and colonization, this simple trait-less inference model is informative and robust to trait effects on colonization, speciation and extinction. Nonetheless, our new simulation model may provide a useful tool for studying patterns of trait variation.

opencc-by-4.0Aug 2022View details →

Diffusion models with time-dependent parameters: "An analysis of computational effort and accuracy of different numerical methods"

Software repository for the reproduction of the test cases from Thomas Richter, Rolf Ulrich, Markus Janczyk: Diffusion models with time-dependent parameters: "An analysis of computational effort and accuracy of different numerical methods" This software is used in particular for the reproducibility of the results. However, the algorithms can also be used directly for own purposes. If you have any questions about possibly necessary adaptations, please contact thomas.richter@ovgu.de. Parts of this repository General setup Python collects all Python script. Here, Python/PythonTools are several internal functions, e.g. the realizations of KFE and random walks. Python/results and Python/pics are the directories where the results (figures and text-files) are put. C++ collects the C++ scripts. Case I Reproduces Case I of the paper (time-independent) <ul> <li>Python/TestCase1.py</li> </ul> runs the test-case with random walks, integral equation method and with KFE. It produces output in Python/pics and Python/results. These results will be used in C++/testcase1.cc (as reference solution) and by Python/TestCase1-Plot.py <ul> <li>C++/testcase1.cc</li> </ul> runs the stochastic Euler simulation. Script is started by C++/run-testcase1.sh. It reads in the reference solution generated by Python/TestCase1.py for computing errors. <ul> <li>Python/TestCase1-Plot.py</li> </ul> produces Fig. 6 of the paper. It requires the outputs of Python/TestCase1.py and C++/testcase1.cc Case II Reproduces Case II of the paper (time-dependent thresholds and drift) <ul> <li>Python/TestCase2.py</li> </ul> runs the test-case with random walks, integral equation method and with KFE. It produces output in Python/pics and Python/results. These results will be used in C++/testcase2.cc (as reference solution) and by Python/TestCase2-Plot.py <ul> <li>C++/testcase2.cc</li> </ul> runs the stochastic Euler simulation. Script is started by C++/run-testcase2.sh. It reads in the reference solution generated by Python/TestCase2.py for computing errors. <ul> <li>Python/TestCase2-Plot.py</li> </ul> produces Fig. 7 of the paper. It requires the outputs of Python/TestCase2.py and C++/testcase2.cc <ul> <li>Python/TestCase2-AdjustRandomWalks.py</li> </ul> runs simulations to reproduce Fig. 11 of the paper and implements the modification of the random walk strategy to limit oscillations. Case III Reproduces Case III of the paper (dependency of the accuracy on the derivative of the drift) <ul> <li>Python/TestCase3.py</li> </ul> runs the test-case with random walks, integral equation method and with KFE for a fixed discretization but with different values of the drift tau. It produces first part of Fig. 8. <ul> <li>C++/testcase3.cc</li> </ul> runs the stochastic Euler simulation. Script is started by C++/run-testcase3.sh. It reads in the reference solution generated by Python/TestCase3.py for computing errors. <ul> <li>Python/TestCase3-Plot.py</li> </ul> produces second part of Fig. 8. Depends on the output of Python/TestCase3.py Case IV Reproduces Case IV of the paper (accuracy and efficiency for Dirac initial data) <ul> <li>Python/TestCase4.py</li> </ul> runs the test-case with random walks, integral equation and with KFE for a refined discretizations. <ul> <li>Python/TestCase4-Plot.py</li> </ul> produces Fig. 9. Depends on the output of Python/TestCase4.py <ul> <li>Python/TestCase4-showsolution.py</li> </ul> Solves with the KFE and plots the solution as surface plot over time and space variable. This skript is used to create Fig. 10 of the paper. Problem parameters and discretization can be adjusted at the top of the script. To test the different stabilization strategies, one can either adjust the value of theta, or one activates Rannacher time-marching by commenting in the marked lines in the skript PythonTools/kfe.py, here in kfe_ale(..) Data Fitting Python scripts to fit the KFE model to the Data published by Rolf Ulrich et al. in R. Ulrich, H. Schröter, H. Leuthold, T. Birngruber Automatic and controlled stimulus processing in conflict tasks: Superimposed diffusion processes and delta functions.Cognitive Psychology, 78 , 148–174 <ul> <li>Python/DataFitting-Simon.py</li> </ul> runs the parameter fitting for the Simon task and produces data for Fig. 9 and Table 1. <ul> <li>Python/Eriksen-Fletcher.py</li> </ul> runs the parameter fitting for the Eriksen Fletcher task and produces data for Fig. 9 and Table 2. Installation & running the examples Python The python skripts can just be started. Just note that they depend on each other, i.e.: Python/TestCase1.py produces a reference solution that is required by C++/testcase1.cc and the results of both are needed in Python/TestCase1-Plot.py The scripts only depend on standard packages like numpy or scipy and all Python environments should work. One suggestion is to use Spyder as part of Anaconda. C++ The C++-programs are not intended for performing the simulations in a stand-alone application. Instead, the SDE is simulated for a given number of trials N_tr and a given time step dt and this simulation is repeated 64 times in order to estimate the average error. It should however be simple to use the scripts as basis for an efficient parallel simulation tool that uses multithreading. Configuration The C++ test cases must be compiled. The test cases are set up to use cmake. We suggest the following (in a Linux-environment or on a Mac using homebrew or MacPorts): <ol> <li>Create a directory for compilation, e.g. C++/bin now called the bin-dir</li> <li>In the bin-dir calls cmake by cmake .. (adjust the path, if the bin-dir is not a subdirectory of the C++-dir.</li> <li>Several options can be adjusted. In C++/bin call ccmake . to make all necessary changes.</li> </ol> If you change the location of the bin-dir you will have to modify the run-scripts run-testcase[123].sh. Compilation Initially and whenever you change the code, the programs must be re-compiled <ol> <li>In C++/bin just call make</li> </ol> Running the examples The programs are started in C++. For each of the test-case there is a skript to start the program. <ol> <li>In C++ call sh ./run-testcase1.sh (or sh ./run-testcase2.sh, etc.)</li> </ol> Each script will start the programs several times. For Case I, Case II and Case IV the simulation is started on a sequence of finer and finer discretizations, for Case III the value of tau will be changed. The scripts store the output in C++/results. Old outputs will be overwritten! Further, the scripts read information about the reference solution from Python/resuts. The C++ programs use multithreading the OpenMP. If you do not specify the number of threads to be used, all available threads are taken including all hyperthreads. This is usually not efficient it is therefore advisable to set the number of threads by hand, e.g. by calling export OMP_NUM_THREADS=8 before calling the run-scripts. License Information Initially the software has been written Thomas Richter, Otto-von-Guericke University Magdeburg, Germany in 2022, 2023 (thomas.richter@ovgu.de) You are free to use the scripts under the Creative Commons Attribution 4.0 License.

opencc-by-4.0Feb 2023View details →

Automatic Specialization of Third-Party Java Dependencies - Experimental Results

This entry contains the experimental results of the research paper titled: Automatic Specialization of Third-Party Java Dependencies. It includes the build results (e.g., executions logs, test results, JAR files, etc.) for the original, debloated, and specialized variants of the dependency trees for the 30 Java project used as study subjects in the paper.

opencc-by-4.0Feb 2023View details →

X-ray scattering datasets associated with the publication "Side chain length dependent dynamics and conductivity in self assembled ion channels"

X-ray scattering datasets for samples described in the 2022 publication "Side chain length dependent dynamics and conductivity in self assembled ion channels". This dataset includes both raw and processed X-ray scattering data for samples ILC8, ILC10, ILC12, ILC14 and ILC16 alongside background measurement files (BKG).