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The data uploaded here are for the manuscript titled 'Astrocyte-derived extracellular vesicles enhance the electrophysiological function and cell survival of human cortical neurons in vitro '
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This dataset contains R script and its supporting files for processing the full-scan spectra obtained from FT-ICR-MS system.
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This file is part of joint work between A. Rasoulzadeh and G. Nawratil at Center for Geometry and Computational Design (GCD), Vienna University of Technology (TU Wien). It is created on October 10th, 2019. ABSTRACT: ‎The class of linear pentapods with a simple singularity variety is obtained by imposing architectural restrictions on the design of a linear pentapod in a way that the manipulator's singularity variety is linear in orientation/position variables‎. ‎It turns out that such a simplification leads to crucial computational advantages while maintaining the machine's applications in some fundamental industrial tasks such as 5-axis milling and laser cutting‎. ‎ ‎Assuming that a singularity-free path between a given start‎- ‎and end-pose of the end-effector within the manipulator's workspace‎ is known,‎ an optimization process of this path is proposed in such a way that the robot increases its distance to the singularity loci‎ while the motion is being smoothed‎. ‎In this case the computation time of the optimization is improved as one deals with the pentapods having a simple singularity variety allowing symbolic solutions for the local extrema of the singularity-distance function‎. The whole process is called variational path optimization and takes place ‎through defining a ‎novel ‎‎cost ‎function‎. ‎This optimization process takes the physical limits of prismatic joints and base spherical joints into account‎‎. HOW TO USE: In order to use the algorithm please type "variational_path_optimization" in the MATLAB "Command Window". The code then asks the user a range of questions from "architectural aspects of your manipulator" to plot options. For most of these questions the user can simply ignore (if he/she does not wish a very specific optimization or plot) by pressing enter. However some of these questions are obligatory to answer. Therefore we ask the user to type "help variational_path_optimization" in in the MATLAB "Command Window" for a thorough description of his/her available options. Please note that a DEFAULT SETTING is made available for the code by which the user can observe how the algorithm works on a predefined simple pentapod and a predefined singularity-free initial motion (as a sample we recommend using the special curve "twisted"). Finally, if the user has access to MAPLE, then he/she can visualize the full results alongside the shape of the manipulator. In order to do so please run "variational_path_optimization.m" on a case, then execute the files "pentapod.mw" and "plot.mw" consecutively. NOTE: 9 videos (GIF files) of motions of a sample is provided for you in the folder "Sample Videos". WARNING: Note that the rest of the MATLAB functions in the folder are just nested functions in the file "variational_path_optimization.m". The help option is also available for all these nested functions which demonstrates their specific role within the main code. The MATLAB files will be subject to minor updates including a GUI
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The program is dedicated to true water color (TWC) calculation by light absorption in visual range from 390 up to 830 nm. Calculation is based on mathematical model of color perception by standard observer using spectral data, contained in text files. It allows: 1 – To load standard solutions and samples spectra with spectrum conversion into absorption when required; 2 – To save and upload calculation of graduation curve and graduation data; 3 – To calculate true water color and export data to Microsoft (MS) Excel table; Surce code and data examples are also attached.
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Field exp 8a gives data for the compression experiment described; field exp 10a gives data for the indentation experiment.
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B6O Nanoindentation Dataset - 24 indentations
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The data series sample cover 2,101 European equity funds, with monthly data for the period January 2001 to October 2016, as provided by Morningstar. We use all funds sorted as Euro/Eurozone equity funds in Morningstar, traded in euros. Specifically, we include the following categories: Europe ex-UK Large-Cap Equity; Europe Equity-Currency Hedged; Europe ex-UK Small/Mid-Cap Equity; Europe Flex-Cap Equity; Europe Large-Cap Blend Equity; Europe Large-Cap Growth Equity; Europe Large-Cap Value Equity; Europe Mid-Cap Equity; Europe Small-Cap Equity; Eurozone Flex-Cap Equity; Eurozone Large-Cap Equity; Eurozone Mid-Cap Equity and Eurozone Small-Cap Equity. We omit those funds that hold exclusively domestic stocks, in order to avoid distorting our results on grounds of risk exposures that involve specific areas. The dataset comprises the following series: 1. Summary statistics for 2,101 Euro/Eurozone equity funds. 2. Summary statistics for 20 size portfolios, formed by 2,101 Euro/Eurozone equity funds. 3. DEA estimates for 20 size portfolios, formed by 2,101 Euro/Eurozone equity funds. 4. Monthly returns for the three classic factors of Fama and French and for the DEA factor. 5. Monthly returns for 20 size portfolios, formed by 2,101 Euro/Eurozone equity funds.
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Mineral wastes utilised for pretreatment of OFMSW, followed by anaerobic digestion at mesophilic temperature of 37oC in lab scale continuous stirred reactor systems (CSTR). Genomic DNA of samples of digestate from these reactors were used for Illumina Hiseq 16S rRNA analysis.
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+ The tested data for Inter-Domain Path Computation under Domain Uniqueness constraint (IDPCDU). + On account of no instances were available for IDPC-DU, we made up our minds to generate a set for test instances to evaluate the proposed algorithms. To generate an instance, we first passed three parameter: number of nodes, number of domains and number of edges. After that, we created an array of distinct nodes and an array of distinct domains that satisfied the number of nodes is greater than the length of domain array. Source nodes and terminal node are the first and the last nodes of the nodes array, respectively. With the above arrays, we merged them to make a valid solution called P. Each edge of P was set to the weight one, except the out-edge of the source node is set to the weight two. To add noise to the test instance, for every single node in P, we added some edges to random nodes not in P. Moreover, we created some one-weighed-edges between the the nodes not in P. These traps would make simple greedy algorithms get it harder to find optimal solution. Eventually, we randomly generated edges that have greater values of weight than the value of the length of P. This method guaranteed that P is the optimal solution of the instance. There were two set of instances created, a small set and a large set. + Filename idpc_xx.idpc First line of a file constains two intergers N and D, which are number of nodes and number of domains, respectively. Second line contains two integers s and t, which are the source node and terminal node. Every next line contains four integers u, v, w, d, represents an edge (u,v) has weight w and belong to domain d.
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"Tb data" contains information on core body temperature for three species of mole-rat (Damaraland, Natal, highveld) at different ambient temperatures "Ts data" contains information on surface body temperatures of different body parts for three species of mole-rat (Damaraland, Natal, highveld) at different ambient temperatures
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