This information provides the data and commands to manually setup the computational simulations used in the PLOS ONE paper 'Patient-specific modeling of right coronary circulation vulnerability post-liver transplant in Alagille’s syndrome' using CRIMSON (CARDIOVASCULAR INTEGRATED MODELLING & SIMULATION) a prototype simulation environment developed under the support of the European Research Council (( http://www.crimson.software/)., Note that a Windows version of the CRIMSON flowsolver is provided as part of the CRIMSON Windows installer, but you will need a very powerful Windows computer to run these simulations, as the models used in the present work are extremely computationally-demanding. It is recommended that you use a Linux version of the CRIMSON flowsolver on a high-performance computer., Option 1 (ready-to-use files to immediately start the simulation):
1. Please unzip the Ready-to-use files.
2. Copy the folders of each of the three conditions to the high performance computer.
3. In addition to different codes used, each folder provides the boundary conditions applied in the simulations described in the manuscript (e.g. LPN parameters). To run the 3D simulations for each condition simply launch the it using the CRIMSON flowsolver. In addition, the solver.inp file can be modified to run a 0D "real-time simulation" (please open solver.inp with a text editor and modify line 4 "Simulate in Purely Zero Dimensions:" to "True")., Option 2 (using the MITK files):
1. Please download and install Crimson software ( http://www.crimson.software/).
2. Please unzip the MITK files and the Ready-to-use files.
3. From amongst the provided MITK files, load the MITK file of interest to CRIMSON (using the MITK files, additional changes can be made to the computational model in case the user wants to explore different settings/boundary conditions e.g. change the vascular wall properties, introducing a change in the geometry to create a virtual stenosis).
3. Navigate to the tree in the "Data Manager" panel and select the "Pulmonaries", "CRIMSON SOLVER" and then "Solver study 3D" items, in the described order.
4. In the right hand panel select the "CRIMSON Solver setup" tab and scroll down the right hand bar until to find the "Setup Solver" box; click to output the simulation files (faceInfo.dat, geombc.dat.1, multidomain.dat, netlist_surface.dat,numstart.dat, presolver folder, solver.inp, restart.0.1).
5. Copy and replace the geombc.dat.1 and restart.0.1 generated by CRIMSON for each individual condition to the respective unziped folder in the Ready-to-use file (discard the remaining files that were output by CRIMSON). Note that if you have not changed anything about the model (e.g. vascular wall properties), then doing this will produce restart.0.1 and geombc.dat.1 files which are identical to the ready-to-use versions.
6. Finally copy each Condition folder to the high performance computer and simply launch the simulation using the CRIMSON flowsolver., and For technical queries please contact email@example.com. --October 2018.
There is a directory tree inside this zipped file. The main directory has the Adobe Illustrator plots of the figures in the paper, Space Weather journal manuscript # 2018SW002067, "Model evaluation guidelines for geomagnetic index predictions" by M. W. Liemohn and coauthors. The three subdirectories have the files for the individual models, the data to which they are compared, and the IDL code used to create the figure plots and metrics calculations. and Date coverage is specific to each model. The RAMSCB model covers January 2005, the WINDMI model all of 2014, and the UPOS model 1.5 solar cycles, from 1 October 2001 through 29 July 2013.
Data include variables used to run accelerated failure time models examining the association between the nose/throat microbiome and 1) symptom duration, 2) shedding duration, and 3) time to infection. Certain individual participant data have been excluded due to identifiability concerns. Data also include the oligotype count table and taxonomic classifications.
Data include variables used to run mixed effects models examining the association between the nose/throat microbiome and influenza virus infection. Certain individual participant data have been excluded due to identifiability concerns. Data also include the oligotype count table and taxonomic classifications. and Curation Notes: Readme updated Nov. 29, 2018 with context for oligotype and taxonomy files, and citation to associated article.
This is the experimental data referenced in our manuscript entitled “SMALL-LABS: An algorithm for measuring single molecule intensity and position in the presence of obscuring backgrounds .” These live-cell single-molecule imaging movies were used as a test of the SMALL-LABS single-molecule image analysis algorithm.
The dataset comprises two movies; each one is provided both as a .tif stack and as an .avi file. The movie called “low_bg” has a standard low background, and the movie called “high_bg” includes a high fluorescent background produced by an external 488-nm laser.
The eastern coastal basins of Brazil are a series of small and isolated rivers that drain directly into the Atlantic Ocean. During the Pleistocene, sea-level retreat caused by glaciations exposed the continental shelf, resulting in enlarged paleodrainages that connected rivers that are isolated today. Using Geographic Information System (GIS), we infer the distribution of these paleodrainages, and their properties for the east Brazilian coast. Here, we publicly make available the shapefiles that demonstrate the paleodrainage structure along the Brazilian coast during the largest sea-level retreats in the Pleistocene, the riverine vectors during the same period and the coastal line for a drop of -125m in the sea.
Percent Weight Change Data:
The model was run continuously on a daily time step for seasonal intervals (Spring: March thru May; Summer: June thru August; Fall: September thru November) as well as contiguously from Spring to Fall to assess total growth over the likely growing season (March thru November). CSV files represent the simulated weight change (%) of Bighead and Silver Carp for the respective time periods associated with the file name. Initial fish mass for each seasonal interval and growing season was 4350 g for Silver Carp and 5480 g for Bighead Carp. Maximum and mean total weight change (%) was determined for three depth ranges (near surface depths [NS]: 0 – 10 m; deep chlorophyll layer depths [DCL]: 10 - 50 m; and whole water column [WC]). Coordinates are in decimal degrees.
File naming convention: speciesSeasonWtChange (e.g. bigheadFallWtChange = % weight change of Bighead Carp from September through November)
Monthly Habitat Quality Data:
Rdata files contain matrices of Bighead or Silver carp growth rate potential as represented as a mass-proportional growth rate (gram of carp/gram of carp/day [g/g/d]) for the 15th day of each month. Habitats with growth rate potential >= 0 g/g/d were deemed suitable.
Rows: Row numbers refer to the spatial node with 20 equally-spaced vertical layers.
Columns: Columns 1-20 refer to the growth rate potential value for each vertical layer of each node. Vertical layers are evenly spaced based on the total depth of the water column for each node. Depth for each node can be found in the grid attributes data file. Columns 21 ("meanG") and 22 ("Gmax") represent the average and maximum growth rate potential, respectively, of the fish across the whole water column for the corresponding node.
File naming convention: species_MonthNumber (e.g. silver_06 = Silver carp growth rate potential in June)
Spatial coordinates for each node can be found in the grid attributes data files.,
Grid attributes data:
This Rdata file provides the spatial reference data and other grid attributes. Coordinates are provided in UTM (x & y) and latitude and longitude (decimal degrees). Depth (meters) for each node is listed in this file.
, GRP Model code:
Details bioenergetics equations, foraging equation, functions for running the model on a monthly time-step and daily time step, and functions for basic analyses. Model is coded in R., and
The simulated input data (prey and temperature) used to run our model is not included in this data set. Instead we provide the model code, grid attributes, and outputs of the model.
The readRDS() function (R Base Package v.3.5.1) is required to read in .Rdata files in R.
Nighttime and diurnal surveys in the lowland Peruvian Amazon of Los Amigos Biological Station were conducted in order to describe herpetological diversity at this site. As a result of these surveys, the predation event between a Pamphobeteus sp. and Marmosops sp. and the myiasis of Ranitomeye uakarii were observed. The video footage was recorded in order to document these interesting interactions between arthropod predators and parasites and vertebrate prey and hosts, and are included for publication in the short communication "Ecological interactions between arthropods and small vertebrates in a lowland Amazon rainforest" in the journal Amphibian and Reptile Conservation.