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  • Data set of DLV code and simulation algorithms of ProPrivacy
    Data Types:
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    • Dataset
    • File Set
  • This data-set contains results from pull-out experiments on small-scale Salix cuttings. The folder "uprooting tests" contains the values of the uprooting force recorded over time. Values of the total root length of each sample are illustrated in an excel file: "max_uprooting_force-root length". The values of the total root surface area of each sample can be found in the folder: "root surface area". Data are divided according to the uprooting time. Data about the above-ground biomass of the samples can be found in the files excel: "cuttings_growth" and "stem_length-volume".
    Data Types:
    • Dataset
    • File Set
  • Amphiphile-based aggregates are extensively used in numerous applications for encapsulation, storage, transport and delivery of toxic, active molecules due to the structural properties of the aggregates. The properties of the aggregates in turn are dictated by the molecular architecture of the amphiphiles. A complete understanding of the multiscale architecture–structure–function relationship for amphiphile-based aggregates requires the simultaneous resolution of the self-assembly of amphiphilic molecules along with an understanding of the role of various long range physical interactions including hydrodynamics. A multiscale computational approach such as the hybrid Molecular Dynamics–Lattice Boltzmann technique is able to fulfill most of those requirements. However, existing implementations only account for static coupling between the Molecular Dynamics technique and the Lattice Boltzmann method, and hence are unable to resolve the changes in the solvent-amphiphile interface during processes such as self-assembly and interfacial adsorption. In this study, a new implementation incorporating a dynamic coupling scheme between the Molecular Dynamics technique and the Lattice Boltzmann method is introduced so as to resolve dynamical changes in interfaces. The application of the new implementation to the self-assembly of phospholipids yields results which are in good agreement with computation, experiments and theory. In particular, we found the scaling exponent α of the cluster number (N(t) = C t^α) to be ~1. The previous version of this program (AEPH_v1_0) may be found at http://dx.doi.org/10.1016/j.cpc.2013.03.024.
    Data Types:
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    • File Set
  • See the paper related to these dataset
    Data Types:
    • Software/Code
    • Image
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  • This repository provides the supplementary R code and data to reproduce the experiments in the following paper : "Highly accurate diagnosis of papillary thyroid carcinomas based on personalized pathways coupled with machine learning ". These include: 1. The main method function R file 2. The main script R file 3. The datasets for the development/validation cohorts (R data file format) 4. The pathway information (R data file format)
    Data Types:
    • Software/Code
    • Dataset
  • We develop a FORTRAN code to compute fluctuations in atomic condensates (FACt) by solving the Bogoliubov–de Gennes (BdG) equations for two component Bose–Einstein condensate (TBEC) in quasi-two dimensions. The BdG equations are recast as matrix equations and solved self consistently. The code is suitable for handling quantum fluctuations as well as thermal fluctuations at temperatures below the critical point of Bose–Einstein condensation. The code is versatile, and the ground state density profile and low energy excitation modes obtained from the code can be easily adapted to compute different properties of TBECs — ground state energy, overlap integral, quasi particle amplitudes of BdG spectrum, dispersion relation and structure factor and other related experimental observables.
    Data Types:
    • Dataset
    • File Set
  • The VOFTools library includes useful tools for performing the geometrical operations that typically arise in volume of fluid (VOF) methods. We present a major improvement of VOFTools to extend its use to non-convex geometries without the need for costly convex-decomposition techniques. A thorough adaptation of the different routines has been carried out to meet the challenges of the new geometries and to maintain, and even improve, the efficiency and robustness of the previous tools. Specifically, we upgraded the routines for (1) truncating a polyhedron with a half space, (2) computing the interface position to cut off a certain volume fraction from a cell in PLIC (piecewise linear interface calculation) reconstruction and (3) computing the volume of a material body, defined by an implicit function, that is contained inside a mesh cell. To assess the performance of the supplied routines, different tests, which are provided in FORTRAN and C, were implemented for several 2D and 3D non-convex geometries.
    Data Types:
    • Dataset
    • File Set
  • Data related to the publication: "A Map of Human Type 1 Diabetes Progression by Imaging Mass Cytometry". Damond N, Engler S, Zanotelli VRT, Schapiro D, Wasserfall CH, Kusmartseva I, Nick HS, Thorel F, Herrera PL, Atkinson MA and Bodenmiller B. Cell Metab. 2019 Mar 5;29(3):755-768.e5. https://doi.org/10.1016/j.cmet.2018.11.014 We used imaging mass cytometry to simultaneously image 37 biomarkers with single-cell and spatial resolution in pancreas sections from 12 human donors at different stages of type 1 diabetes. CODE: - Python script for coordinate transformation - Functions for custom histoCAT neighborhood analysis DATA: - Single-cell data - Islet-level data - Cell type information - Cell relationships (cell-cell neighborhoods and cell-islet relationships) - Donors and image metadata. - Subset containing the data for 100 images from 3 donors IMAGES: - Image stacks (37 channels) for all donors (one .7z file per donor, numbers indicate nPOD case IDs) - Cell masks - Panel file with information related to antibodies and metal tags - Metadata file linking donor information to images - Metadata file linking image stack slices and panel information - Subset containing 100 images from 3 donors
    Data Types:
    • Software/Code
    • Tabular Data
    • Dataset
    • File Set
  • Data set for 'SPACE SYNTAX AND THE HISTORIC URBAN CORE OF ŁÓDŹ' article Author: Mariusz Lamprecht, PhD, Institute of the Built Environment and Spatial Policy, Faculty of Geographical Sciences, University of Łódź mariusz.lamprecht@geo.uni.lodz.pl
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    • Software/Code
    • Geospatial Data
    • Tabular Data
    • Dataset
    • Document
    • File Set
  • This dataset contains information from the Colombian (2016-2017) Time-Use Survey (ENUT in Spanish) and Mexican (2014)Time-Use Survey. It contains unpaid housework and income information, at the household level, of "pure" working-class households, i.e., households with only waged workers.
    Data Types:
    • Software/Code
    • Tabular Data
    • Dataset