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  • LAMMPS input scripts and sheet models. (1) Two scripts of the cylindrical and spherical confining; (2) Different size of GO sheets model.
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  • This dataset contains all the water leakage images used in this study.
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  • The study aimed at stabilizing the curcumin emulsions (CEs) using the soybean seed oil bodies (SSOBs) and investigated the gastrointestinal digestion of the CEs. The particle size decreased (P < 0.05) with the increasing concentration of SSOBs from 1.0 wt.% to 5.0 wt.%. The CEs stabilized with the SSOBs exhibited excellent stability at pH 2.0 and 6.0-10.0. The CEs were stable against the aggregation at 100-500 mmol/L NaCl concentration and elevated temperature. The droplet size analysis and confocal laser scanning microscope observation results indicated that the fat droplets aggregated in the CEs under the gastric conditions at 30 min and afterward it gradually dispersed. Under the simulated intestinal condition, the droplet size of the CEs significantly decreased compared to the simulated gastric conditions (P < 0.05). The release rate of curcumin continuously increased during 180 min digestion under the intestinal conditions. Therefore, SSOBs could be used as the natural emulsifiers and novel carriers in delivering the lipophilic bioactive compounds.
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  • This compressed file contains all the supporting files to replicate tables and figures in our paper. Please refer to the readme.pdf file for further instructions and cite this material accordingly.
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  • X-Ray Diffraction Patterns of disoriented preparations (bulk rock and clay fractions) and oriented preparations (clay fractions) from samples used in the paper. Na - samples after dissolution of carbonates with sodium acetate–acetic acid buffer treatment. HD - samples after dissolution of carbonates and dissolution of free iron (hydr)oxied with buffered sodium dithionite – citrate – bicarbonate treatment. KD - samples after dissolution of carbonates and dissolution of kaolinite with hot NaOH treatment. Oriented preparations: Air - samples in the air-dry state; GLY - samples after glycolation.
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  • This data set provides the original input data for magma production rate along arc strike, as well as codes and final calculation results.
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  • shield tunnel leakage
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  • We present a program for solving exactly the general pairing Hamiltonian based on diagonalization. The program generates the seniority-zero shell-model-like basis vectors via the ‘01’ inversion algorithm. The Hamiltonian matrix is constructed in this seniority-zero space. The program evaluates all non-zero elements of the Hamiltonian matrix “on the fly” using the scattering operator and a search algorithm. The matrix is diagonalized by using the iterative Lanczos algorithm. The OpenMP parallel program thus developed, PairDiag, can efficiently calculate the ground-state eigenvalue and eigenvector of the general pairing Hamiltonian for both the even-mass and the odd-mass system. The program is packaged in a Fortran module, which makes it easy to use the program to replace the BCS approximation in standard self-consistent mean field calculations. For systems with dimension around 10^8, the calculation can be done within hours on standard desktop computers.
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  • Time segmentation DBLP dataset is divided into eleven time windows (time span 01/01/2003 to 31/12/2013). Facebook Wall Posts dataset is divided into eight time windows (time span 01/01/2005 to 31/12/2008). Wiki-Talk dataset is segmented into six time windows (time span 24/11/2007 to 31/12/2007). Enron email dataset is segmented into twelve time windows (time span 01/01/2001 to 31/12/2001). Reddit-reply dataset is segmented into six time windows (time span 07/01/2014 to 13/01/2014). Stack Overflow dataset is segmented into six time windows (time span 24/01/2016 to 29/02/2016). Social group discovery Communities of each time window are discovered using Infomap, Label Propagation, and Leiden algorithms. For running the community detection algorithms, we assume that the datasets are undirected and unweighted graphs. The communities whose size was smaller than two members were ignored. Community evolution tracking and chain identification In order to track community evolution, we investigate each community to find its similar community or communities from previous time windows, which is called community matching. We employed ICEM (Identification of Community Evolution by Mapping) (Kadkhoda Mohammadmosaferi & Naderi, 2020) method in order to determine the evolution events because it is a highly efficient approach to track community evolution and considers partial evolution and non-consecutive time windows. ICEM has two parameters which are α and β, in this paper, the thresholds for being partially similar and very similar are set to α=10% and β=90%, respectively. Each uploaded dataset contains chains of evolution for a community detection algorithm. Reference: Kadkhoda Mohammadmosaferi, K., Naderi, H., 2020. Evolution of communities in dynamic social networks: An efficient map-based approach. Expert Syst. Appl. 147, 113221.
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  • 1) To calculate the average volume expansion coefficient reference data of liquid densities in the range of 20–50 °C were used, and the entropy was calculated for the middle of the specified interval (35 °C). 2) Calculations of the moments of inertia were made as follows. Initially, for a conformer (if a conformational isomerism was possible for the compound) with minimal energy, a nonempirical calculation of optimized atomic coordinates was performed using the GAMESS software package (ver. 2018-R1-pgi-mkl, the Hartree-Fock method, basis 6-31G*), which was then used to calculate moments of inertia in the program "Moments of inertia" written specially for this purpose. The correctness of the results obtained was verified (for those compounds for which it was possible) by comparison with the database of computational chemistry and comparative tests of the National Institute of Standards and Technology (NIST).
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